diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..5f37ac3 --- /dev/null +++ b/.gitignore @@ -0,0 +1,38 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ + +dev/ +results/ +wandb/ +.ipynb_checkpoints/ +.vscode/ +.cache +local/ +outputs/ + +*.pt +*.ckpt + +# Logs +logs/ +*.log +results/ +runs/ +dev* +local/ +generated/ + +.DS_Store +pretrained_models/ + +*.err +*.out + +# Dev +dev/ + +# Data +data/ +outputs/ +deploy/ +.gradio/ \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..3ac37aa --- /dev/null +++ b/README.md @@ -0,0 +1,179 @@ +
+

🎤 SoulX-Singer

+

+ Official inference code for
+ SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis +

+

+ SoulX-Logo +

+

+ Demo Page + GitHub + Technical Report + License +

+
+ +--- + +## 🎵 Overview + +**SoulX-Singer** is a high-fidelity, zero-shot singing voice synthesis model that enables users to generate realistic singing voices for unseen singers. +It supports **melody-conditioned (F0 contour)** and **score-conditioned (MIDI notes)** control for precise pitch, rhythm, and expression. + +--- + +## ✨ Key Features + +- **🎤 Zero-Shot Singing** – Generate high-fidelity voices for unseen singers, no fine-tuning needed. +- **🎵 Flexible Control Modes** – Melody (F0) and Score (MIDI) conditioning. +- **📚 Large-Scale Dataset** – 42,000+ hours of aligned vocals, lyrics, notes across Mandarin, English, Cantonese. +- **🧑‍🎤 Timbre Cloning** – Preserve singer identity across languages, styles, and edited lyrics. +- **✏️ Singing Voice Editing** – Modify lyrics while keeping natural prosody. +- **🌐 Cross-Lingual Synthesis** – High-fidelity synthesis by disentangling timbre from content. + +--- + +

+ Performance Radar +

+ +--- + +## 🎬 Demo Examples + +
+ Demo 1

+ Demo 2 +
+ +--- + +## 📰 News + +- **[2026-02-06]** SoulX-Singer inference code and models released. + +--- + +## 🚀 Quick Start + +### 1. Clone Repository + +```bash +git clone https://github.com/Soul-AILab/SoulX-Singer.git +cd SoulX-Singer +``` + +### 2. Set Up Environment + +**1. Install Conda** (if not already installed): https://docs.conda.io/en/latest/miniconda.html + +**2. Create and activate a Conda environment:** +``` +conda create -n soulxsinger -y python=3.10 +conda activate soulxsinger +``` +**3. Install dependencies:** +``` +pip install -r requirements.txt +``` +⚠️ If you are in mainland China, use a PyPI mirror: +``` +pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com +``` + + +--- + +### 3. Download Pretrained Models + +Install Hugging Face Hub if needed: + +``` +pip install -U huggingface_hub +``` + +Download the SVS model and preprocessing models: +```sh +pip install -U huggingface_hub + +# Download the SoulX-Singer SVS model +hf download Soul-AILab/SoulX-Singer --local-dir pretrained_models/SoulX-Singer + +# Download models required for preprocessing +hf download Soul-AILab/SoulX-Singer-Preprocess --local-dir pretrained_models/SoulX-Singer-Preprocess +``` + + +### 4. Run the Demo + +Run the inference demo: +``` sh +bash example/infer.sh +``` + +This script relies on metadata generated from the preprocessing pipeline, including vocal separation and transcription. Users should follow the steps in [preprocess](preprocess/README.md) to prepare the necessary metadata before running the demo with their own data. + + +## 🚧 Roadmap + +- [ ] 🖥️ Web-based UI for easy and interactive inference +- [ ] 🌐 Online demo deployment on Hugging Face Spaces +- [ ] 📊 Release the SoulX-Singer-Eval benchmark +- [ ] 📚 Comprehensive tutorials and usage documentation + + +## 🙏 Acknowledgements + +Special thanks to the following open-source projects: + +- [F5-TTS](https://github.com/SWivid/F5-TTS) +- [Amphion](https://github.com/open-mmlab/Amphion/tree/main) +- [Music Source Separation Training](https://github.com/ZFTurbo/Music-Source-Separation-Training) +- [Lead Vocal Separation](https://huggingface.co/becruily/mel-band-roformer-karaoke) +- [Vocal Dereverberation](https://huggingface.co/anvuew/dereverb_mel_band_roformer) +- [RMVPE](https://github.com/Dream-High/RMVPE) +[Paraformer](https://modelscope.cn/models/iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch) +- [Parakeet-tdt-0.6b-v2](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2) +- [ROSVOT](https://github.com/RickyL-2000/ROSVOT) + + + +## 📄 License + +We use the Apache 2.0 license. Researchers and developers are free to use the codes and model weights of our SoulX-Singer. Check the license at [LICENSE](LICENSE) for more details. + + +## ⚠️ Usage Disclaimer + +SoulX-Singer is intended for academic research, educational purposes, and legitimate applications such as personalized singing synthesis and assistive technologies. + +Please note: + +- 🎤 Respect intellectual property, privacy, and personal consent when generating singing content. +- 🚫 Do not use the model to impersonate individuals without authorization or to create deceptive audio. +- ⚠️ The developers assume no liability for any misuse of this model. + +We advocate for the responsible development and use of AI and encourage the community to uphold safety and ethical principles. For ethics or misuse concerns, please contact us. + + +## 📬 Contact Us + +We welcome your feedback, questions, and collaboration: + +- **Email**: qianjiale@soulapp.cn | menghao@soulapp.cn | wangxinsheng@soulapp.cn + +- **Join discussions**: WeChat or Soul APP groups for technical discussions and updates: + +

+ + +
+ + WeChat Group QR Code + + +

\ No newline at end of file diff --git a/assets/performance_radar.png b/assets/performance_radar.png new file mode 100644 index 0000000..e82144e Binary files /dev/null and b/assets/performance_radar.png differ diff --git a/assets/soul_wechat01.jpg b/assets/soul_wechat01.jpg new file mode 100644 index 0000000..f7554cf Binary files /dev/null and b/assets/soul_wechat01.jpg differ diff --git a/assets/soulx-logo.png b/assets/soulx-logo.png new file mode 100644 index 0000000..a616ff7 Binary files /dev/null and b/assets/soulx-logo.png differ diff --git a/assets/technical-report.pdf b/assets/technical-report.pdf new file mode 100644 index 0000000..e4f42ee Binary files /dev/null and b/assets/technical-report.pdf differ diff --git a/cli/inference.py b/cli/inference.py new file mode 100644 index 0000000..d91926b --- /dev/null +++ b/cli/inference.py @@ -0,0 +1,147 @@ +import os +import torch +import json +import argparse +from tqdm import tqdm +import numpy as np +import soundfile as sf +from collections import OrderedDict +from omegaconf import DictConfig + +from soulxsinger.utils.file_utils import load_config +from soulxsinger.models.soulxsinger import SoulXSinger +from soulxsinger.utils.data_processor import DataProcessor + + +def build_model( + model_path: str, + config: DictConfig, + device: str = "cuda", +): + """ + Build the model from the pre-trained model path and model configuration. + + Args: + model_path (str): Path to the checkpoint file. + config (DictConfig): Model configuration. + device (str, optional): Device to use. Defaults to "cuda". + + Returns: + Tuple[torch.nn.Module, torch.nn.Module]: The initialized model and vocoder. + """ + + if not os.path.isfile(model_path): + raise FileNotFoundError( + f"Model checkpoint not found: {model_path}. " + "Please download the pretrained model and place it at the path, or set --model_path." + ) + model = SoulXSinger(config).to(device) + print("Model initialized.") + print("Model parameters:", sum(p.numel() for p in model.parameters()) / 1e6, "M") + + checkpoint = torch.load(model_path, weights_only=False, map_location=device) + if "state_dict" not in checkpoint: + raise KeyError( + f"Checkpoint at {model_path} has no 'state_dict' key. " + "Expected a checkpoint saved with model.state_dict()." + ) + model.load_state_dict(checkpoint["state_dict"], strict=True) + + model.eval() + model.to(device) + print("Model checkpoint loaded.") + + return model + + +def process(args, config, model: torch.nn.Module): + """Run the full inference pipeline given a data_processor and model. + """ + if args.control not in ("melody", "score"): + raise ValueError(f"control must be 'melody' or 'score', got: {args.control}") + + print(f"prompt_metadata_path: {args.prompt_metadata_path}") + print(f"target_metadata_path: {args.target_metadata_path}") + + os.makedirs(args.save_dir, exist_ok=True) + data_processor = DataProcessor( + hop_size=config.audio.hop_size, + sample_rate=config.audio.sample_rate, + phoneset_path=args.phoneset_path, + device=args.device, + ) + + with open(args.prompt_metadata_path, "r", encoding="utf-8") as f: + prompt_meta_list = json.load(f) + if not prompt_meta_list: + raise ValueError("Prompt metadata is empty. Please run preprocess on prompt audio first.") + prompt_meta = prompt_meta_list[0] # load the first segment as the prompt + with open(args.target_metadata_path, "r", encoding="utf-8") as f: + target_meta_list = json.load(f) + infer_prompt_data = data_processor.process(prompt_meta, args.prompt_wav_path) + + assert len(target_meta_list) > 0, "No target segments found in the target metadata." + generated_len = int(target_meta_list[-1]["time"][1] / 1000 * config.audio.sample_rate) + generated_merged = np.zeros(generated_len, dtype=np.float32) + + for idx, target_meta in enumerate( + tqdm(target_meta_list, total=len(target_meta_list), desc="Inferring segments"), + ): + start_sample_idx = int(target_meta["time"][0] / 1000 * config.audio.sample_rate) + end_sample_idx = int(target_meta["time"][1] / 1000 * config.audio.sample_rate) + infer_target_data = data_processor.process(target_meta, None) + + infer_data = { + "prompt": infer_prompt_data, + "target": infer_target_data, + } + + with torch.no_grad(): + generated_audio = model.infer( + infer_data, + auto_shift=args.auto_shift, + pitch_shift=args.pitch_shift, + n_steps=config.infer.n_steps, + cfg=config.infer.cfg, + control=args.control, + ) + + generated_audio = generated_audio.squeeze().cpu().numpy() + generated_merged[start_sample_idx : start_sample_idx + generated_audio.shape[0]] = generated_audio + + merged_path = os.path.join(args.save_dir, "generated.wav") + sf.write(merged_path, generated_merged, 24000) + print(f"Generated audio saved to {merged_path}") + + +def main(args, config): + model = build_model( + model_path=args.model_path, + config=config, + device=args.device, + ) + process(args, config, model) + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--device", type=str, default="cuda") + parser.add_argument("--model_path", type=str, default='pretrained_models/soulx-singer/model.pt') + parser.add_argument("--config", type=str, default='soulxsinger/config/soulxsinger.yaml') + parser.add_argument("--prompt_wav_path", type=str, default='example/audio/zh_prompt.wav') + parser.add_argument("--prompt_metadata_path", type=str, default='example/metadata/zh_prompt.json') + parser.add_argument("--target_metadata_path", type=str, default='example/metadata/zh_target.json') + parser.add_argument("--phoneset_path", type=str, default='soulxsinger/utils/phoneme/phone_set.json') + parser.add_argument("--save_dir", type=str, default='outputs') + parser.add_argument("--auto_shift", action="store_true") + parser.add_argument("--pitch_shift", type=int, default=0) + parser.add_argument( + "--control", + type=str, + default="melody", + choices=["melody", "score"], + help="Control mode: melody or score only", + ) + args = parser.parse_args() + + config = load_config(args.config) + main(args, config) diff --git a/example/audio/en_prompt.json b/example/audio/en_prompt.json new file mode 100644 index 0000000..e43f9fa --- /dev/null +++ b/example/audio/en_prompt.json @@ -0,0 +1,16 @@ +[ + { + "index": "vocal_5220_10280", + "language": "English", + "time": [ + 5220, + 10280 + ], + "duration": "0.24 0.36 0.30 0.78 0.24 0.56 0.19 0.53 0.36 0.20 0.32 0.57 0.19 0.22", + "text": " Ooh Ooh I wish nothing nothing more more the best best ", + "phoneme": " en_UW1 en_UW1 en_AY1 en_W-IH1-SH en_N-AH1-TH-IH0-NG en_N-AH1-TH-IH0-NG en_M-AO1-R en_M-AO1-R en_DH-AH0 en_B-EH1-S-T en_B-EH1-S-T ", + "note_pitch": "0 63 65 0 65 67 68 62 62 64 67 67 65 0", + "note_type": "1 2 3 1 2 2 2 3 2 3 2 2 3 1", + "f0": "0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 345.2 343.1 341.6 339.8 337.8 331.9 319.5 312.1 310.8 312.6 315.1 316.1 315.3 314.6 315.3 317.9 322.0 329.6 337.5 344.7 347.5 347.2 344.3 339.5 338.2 341.7 342.8 342.2 340.7 343.0 342.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 347.0 345.3 348.7 350.2 350.9 350.3 344.7 340.3 338.3 338.0 342.8 347.4 348.3 346.7 343.4 339.5 340.5 345.2 350.4 357.7 367.3 376.6 385.9 392.6 393.6 389.9 384.7 381.8 382.0 383.0 380.6 373.5 367.9 377.0 385.4 391.4 393.8 395.6 396.1 397.2 399.8 406.0 413.5 416.1 416.0 414.4 413.5 412.9 415.5 418.9 417.5 408.8 389.2 373.9 0.0 0.0 0.0 288.5 286.0 284.2 285.6 288.9 291.3 293.5 294.5 295.2 297.8 299.5 301.0 303.0 305.9 306.8 306.0 304.4 301.8 301.0 300.8 301.8 310.2 309.8 308.2 305.9 303.6 301.5 299.3 298.5 300.0 302.1 303.5 303.6 302.2 299.7 297.5 296.3 296.4 296.8 298.6 302.6 311.8 322.0 333.8 349.0 368.8 393.3 407.1 410.7 407.0 402.3 401.2 401.7 403.9 405.7 403.5 396.8 387.4 378.6 377.8 381.4 384.0 384.7 383.5 382.5 380.8 377.3 378.4 383.5 390.0 392.7 390.5 387.6 385.3 382.7 381.0 382.8 383.9 382.2 379.6 379.3 380.2 383.1 386.0 386.5 385.4 384.3 383.7 384.4 386.2 388.2 388.5 385.0 378.6 360.4 333.7 328.2 332.4 340.2 348.9 339.6 334.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" + } +] \ No newline at end of file diff --git a/example/audio/en_prompt.mp3 b/example/audio/en_prompt.mp3 new file mode 100644 index 0000000..644a4dd Binary files /dev/null and b/example/audio/en_prompt.mp3 differ diff --git a/example/audio/en_target.json b/example/audio/en_target.json new file mode 100644 index 0000000..13d0752 --- /dev/null +++ b/example/audio/en_target.json @@ -0,0 +1,16 @@ +[ + { + "index": "vocal_0_6900", + "language": "English", + "time": [ + 0, + 6900 + ], + "duration": "0.16 0.24 0.32 0.15 0.17 0.24 0.15 0.44 0.29 0.32 0.24 0.32 0.22 0.18 0.24 0.25 1.01 0.26 0.48 0.29 0.79 0.14", + "text": " Who says you're you're not pretty pretty Who says you're you're not beautiful beautiful Who says says ", + "phoneme": " en_HH-UW1 en_S-EH1-Z en_Y-UH1-R en_Y-UH1-R en_N-AA1-T en_P-R-IH1-T-IY0 en_P-R-IH1-T-IY0 en_HH-UW1 en_S-EH1-Z en_Y-UH1-R en_Y-UH1-R en_N-AA1-T en_B-Y-UW1-T-AH0-F-AH0-L en_B-Y-UW1-T-AH0-F-AH0-L en_HH-UW1 en_S-EH1-Z en_S-EH1-Z ", + "note_pitch": "0 68 67 65 63 63 66 67 70 66 68 67 65 63 63 67 65 63 65 61 58 0", + "note_type": "1 2 2 2 3 2 2 1 3 1 2 2 2 3 2 2 3 1 2 2 3 1", + "f0": "0.0 0.0 382.7 387.7 385.9 379.8 376.0 380.9 390.1 403.2 415.3 423.6 421.6 402.6 385.2 381.1 0.0 0.0 425.8 419.0 409.6 397.8 392.2 389.0 388.5 391.4 389.1 381.4 375.9 0.0 0.0 0.0 0.0 359.0 354.7 353.8 353.7 354.7 353.1 351.1 350.4 349.0 348.9 346.3 337.4 328.0 312.8 303.1 298.4 296.0 298.9 302.0 306.3 307.9 307.3 307.5 307.3 302.9 301.8 0.0 0.0 0.0 0.0 0.0 343.7 364.3 375.9 368.5 358.1 359.1 365.9 378.4 393.1 406.0 412.5 410.9 407.0 404.1 403.5 403.4 401.5 399.4 397.7 395.4 394.4 394.8 395.5 396.5 397.5 400.8 407.9 415.1 417.8 453.1 472.2 481.0 482.3 481.9 480.8 478.7 477.4 476.8 474.8 467.5 446.0 390.4 382.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 374.3 375.5 370.9 370.7 373.1 378.3 392.2 407.6 418.5 423.9 423.2 415.9 395.4 0.0 0.0 0.0 421.5 416.2 405.3 391.0 383.1 380.8 383.0 388.3 388.8 378.3 371.7 0.0 0.0 0.0 371.4 365.1 362.7 358.5 353.0 352.0 353.5 356.1 356.4 353.6 348.3 341.1 330.6 317.7 303.8 293.3 296.5 297.7 301.4 305.3 308.8 308.8 308.2 308.2 306.3 305.6 285.0 269.8 265.6 280.0 304.4 331.2 351.0 357.9 364.2 370.6 381.1 392.9 399.0 399.1 395.0 389.5 379.9 363.0 338.9 318.5 305.6 300.3 299.6 296.3 292.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 309.6 322.1 329.8 331.2 332.1 332.6 332.4 335.4 340.7 345.0 347.2 346.2 342.6 339.6 337.4 338.3 340.9 342.6 344.0 344.6 344.0 344.2 343.6 341.9 338.8 336.7 337.6 341.1 347.0 350.4 343.0 326.6 330.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 310.0 315.7 317.7 317.4 316.5 314.4 314.1 322.5 336.3 350.0 354.2 352.9 350.5 348.4 347.1 347.3 348.4 349.8 349.8 350.4 350.3 323.9 324.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 297.3 289.8 279.5 275.1 276.1 276.1 274.9 275.4 274.6 271.8 268.6 264.0 258.3 251.7 244.3 239.9 236.1 233.7 234.0 236.0 237.3 236.9 235.2 233.5 231.7 231.0 232.1 233.6 235.4 236.2 236.7 235.8 234.1 232.2 231.3 232.6 233.5 235.2 236.0 232.3 228.8 229.6 233.8 241.3 239.4 226.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" + } +] \ No newline at end of file diff --git a/example/audio/en_target.mp3 b/example/audio/en_target.mp3 new file mode 100644 index 0000000..b6eb34f Binary files /dev/null and b/example/audio/en_target.mp3 differ diff --git a/example/audio/music.json b/example/audio/music.json new file mode 100644 index 0000000..bbb6eb7 --- /dev/null +++ b/example/audio/music.json @@ -0,0 +1,16 @@ +[ + { + "index": "vocal_240_51240", + "language": "Mandarin", + "time": [ + 240, + 51240 + ], + "duration": "0.21 0.18 0.34 0.38 0.26 0.22 0.50 0.20 0.33 0.13 0.60 0.22 0.38 0.52 0.30 0.12 1.82 0.98 0.20 0.26 0.38 0.36 0.58 0.54 0.26 0.50 1.46 3.03 0.24 0.24 0.29 0.25 0.20 0.14 0.80 0.22 0.54 0.30 0.24 0.16 0.58 0.28 0.38 1.73 0.79 0.24 0.30 0.34 0.30 0.30 0.34 0.21 0.21 0.36 0.34 0.23 1.85 1.90 0.23 0.39 0.68 0.50 0.31 0.43 0.76 0.38 2.00 1.87 0.68 0.72 0.56 0.62 0.80 0.40 0.42 1.68 1.79 0.70 0.66 0.54 0.24 0.48 0.68 0.40 2.34 0.14", + "text": " 只 是 因 为 为 在 人 群 群 中 多 看 了 你 一 眼 再 也 没 能 忘 掉 你 容 颜 梦 想 着 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0.20 0.32 0.94", + "text": " 像 我 这 样 懦 懦 弱 的 人 人 凡 事 都 要 留 留 几 分", + "phoneme": " zh_xiang4 zh_wo3 zh_zhe4 zh_yang4 zh_nuo4 zh_nuo4 zh_ruo4 zh_de5 zh_ren2 zh_ren2 zh_fan2 zh_shi4 zh_dou1 zh_yao4 zh_liu2 zh_liu2 zh_ji3 zh_fen1", + "note_pitch": "0 50 53 55 53 56 54 53 50 51 53 0 51 53 55 53 54 56 51 53", + "note_type": "1 2 2 2 2 2 3 2 2 2 3 1 2 2 2 2 2 3 2 2", + "f0": "0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 132.7 137.2 144.9 147.0 148.0 148.6 148.9 148.5 147.9 147.4 148.1 149.1 154.3 166.4 173.1 175.0 176.3 175.9 172.7 173.6 175.9 172.9 159.1 165.8 0.0 214.2 213.4 210.2 201.5 198.1 197.1 197.2 197.8 200.8 206.4 206.1 200.5 189.9 180.6 172.0 170.8 171.4 176.2 180.9 182.3 182.2 181.0 180.5 183.4 192.6 211.8 220.6 223.7 219.3 211.9 207.0 203.6 202.6 204.2 204.4 204.1 202.1 198.0 192.9 185.9 177.9 174.1 174.6 174.5 173.8 173.6 172.4 168.3 168.3 172.7 173.2 171.9 170.7 170.2 169.9 170.6 173.1 172.4 164.2 148.2 147.8 152.3 148.5 143.8 145.6 149.2 149.9 150.1 152.5 153.6 154.7 156.1 155.0 152.4 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144.8 0.0 0.0 0.0 0.0 0.0 0.0 181.1 178.9 178.0 177.5 176.0 173.2 172.9 172.9 174.1 176.2 177.3 178.7 178.8 176.0 175.2 175.1 176.3 178.1 177.6 177.4 177.9 177.6 177.3 177.3 177.5 176.6 175.7 176.6 177.5 177.2 175.9 174.8 173.5 174.0 175.7 177.4 177.8 174.7" + } +] \ No newline at end of file diff --git a/example/audio/zh_target.mp3 b/example/audio/zh_target.mp3 new file mode 100644 index 0000000..ff3fe30 Binary files /dev/null and b/example/audio/zh_target.mp3 differ diff --git a/example/infer.sh b/example/infer.sh new file mode 100644 index 0000000..a39661e --- /dev/null +++ b/example/infer.sh @@ -0,0 +1,28 @@ +#!/bin/bash + +script_dir=$(dirname "$(realpath "$0")") +root_dir=$(dirname "$script_dir") + +cd $root_dir || exit +export PYTHONPATH=$root_dir:$PYTHONPATH + +model_path=pretrained_models/SoulX-Singer/model.pt +config=soulxsinger/config/soulxsinger.yaml +prompt_wav_path=example/audio/zh_prompt.mp3 +prompt_metadata_path=example/audio/zh_prompt.json +target_metadata_path=example/audio/music.json +phoneset_path=soulxsinger/utils/phoneme/phone_set.json +save_dir=example/generated/music +control=score # melody or score + +python -m cli.inference \ + --device cuda \ + --model_path $model_path \ + --config $config \ + --prompt_wav_path $prompt_wav_path \ + --prompt_metadata_path $prompt_metadata_path \ + --target_metadata_path $target_metadata_path \ + --phoneset_path $phoneset_path \ + --save_dir $save_dir \ + --auto_shift \ + --pitch_shift 0 \ No newline at end of file diff --git a/example/preprocess.sh b/example/preprocess.sh new file mode 100644 index 0000000..bd6b4ce --- /dev/null +++ b/example/preprocess.sh @@ -0,0 +1,41 @@ +#!/bin/bash + +script_dir=$(dirname "$(realpath "$0")") +root_dir=$(dirname "$script_dir") + +cd $root_dir || exit +export PYTHONPATH=$root_dir:$PYTHONPATH + +device=cuda + + +####### Run Prompt Annotation ####### +audio_path=example/audio/zh_prompt.mp3 +save_dir=example/transcriptions/zh_prompt +language=Mandarin +vocal_sep=False +max_merge_duration=30000 + +python -m preprocess.pipeline \ + --audio_path $audio_path \ + --save_dir $save_dir \ + --language $language \ + --device $device \ + --vocal_sep $vocal_sep \ + --max_merge_duration $max_merge_duration + + +####### Run Target Annotation ####### +audio_path=example/audio/music.mp3 +save_dir=example/transcriptions/music +language=Mandarin +vocal_sep=True +max_merge_duration=60000 + +python -m preprocess.pipeline \ + --audio_path $audio_path \ + --save_dir $save_dir \ + --language $language \ + --device $device \ + --vocal_sep $vocal_sep \ + --max_merge_duration $max_merge_duration \ No newline at end of file diff --git a/preprocess/README.md b/preprocess/README.md new file mode 100644 index 0000000..22d9304 --- /dev/null +++ b/preprocess/README.md @@ -0,0 +1,125 @@ +# 🎵 SoulX-Singer-Preprocess + +This part offers a comprehensive **singing transcription and editing toolkit** for real-world music audio. It provides the pipeline from vocal extraction to high-level annotation optimized for SVS dataset construction. By integrating state-of-the-art models, it transforms raw audio into structured singing data and supports the **customizable creation and editing of lyric-aligned MIDI scores**. + + +## ✨ Features + +The toolkit includes the following core modules: + +- 🎤 **Clean Dry Vocal Extraction** + Extracts the lead vocal track from polyphonic music audio and dereverberation. + +- 📝 **Lyrics Transcription** + Automatically transcribes lyrics from clean vocal. + +- 🎶 **Note Transcription** + Converts singing voice into note-level representations for SVS. + +- 🎼 **MIDI Editor** + Supports customizable creation and editing of MIDI scores integrated with lyrics. + + +## 📁 Data Preparation + +To ensure the data processing pipeline runs correctly, please verify that all required checkpoints are correctly placed in `pretrained_models/SoulX-Singer-Preprocess` + +Before running the pipeline, prepare the following inputs: + +- **Prompt audio** + Reference audio that provides timbre and style + +- **Target audio** + Original vocal or music audio to be processed and transcribed. + +Configure the corresponding parameters in: + +``` +example/preprocess.sh +``` + +Typical configuration includes: +- Input / output paths +- Module enable switches + +## 🚀 Usage + +After configuring `preprocess.sh`, run the transcription pipeline with: + +```bash +bash example/preprocess.sh +``` + +The script will automatically execute the following steps: + +1. **Vocal separation and dereverberation** +2. **F0 extraction and voice activity detection (VAD)** +3. **Lyrics transcription** +4. **Note transcription** + +--- + +After the pipeline completes, you will obtain **SoulX-Singer–style metadata** that can be directly used for Singing Voice Synthesis (SVS). + +⚠️ **Important Note** + +Transcription errors—especially in **lyrics** and **note annotations**—can significantly affect the final SVS quality. We **strongly recommend manually reviewing and correcting** the generated metadata before inference. + +To support this, we provide a **MIDI Editor** for editing lyrics, phoneme alignment, note pitches, and durations. The workflow is: + +**Export metadata to MIDI** → edit in the MIDI Editor → **Import edited MIDI back to metadata** for SVS. + +--- + +#### Step 1: Metadata → MIDI (for editing) + +Convert SoulX-Singer metadata to a MIDI file so you can open it in the MIDI Editor: + +```bash +preprocess_root=example/transcriptions/music + +python -m preprocess.tools.midi_parser \ + --meta2midi \ + --meta "${preprocess_root}/metadata.json" \ + --midi "${preprocess_root}/vocal.mid" +``` + +#### Step 2: Edit in the MIDI Editor + +Open the MIDI Editor (see [MIDI Editor Tutorial](tools/midi_editor/README.md)), load `vocal.mid`, and correct lyrics, pitches, or durations as needed. Save the result as e.g. `vocal_edited.mid`. + +#### Step 3: MIDI → Metadata (for SoulX-Singer inference) + +Convert the edited MIDI back into SoulX-Singer-style metadata (and cut wavs) for SVS: + +```bash +python -m preprocess.tools.midi_parser \ + --midi2meta \ + --midi "${preprocess_root}/vocal_edited.mid" \ + --meta "${preprocess_root}/edit_metadata.json" \ + --vocal "${preprocess_root}/vocal.wav" \ +``` + +Use `edit_metadata.json` (and the wavs under `edit_cut_wavs`) as the target metadata in your inference pipeline. + + +## 🔗 References & Dependencies + +This project builds upon the following excellent open-source works: + +### 🎧 Vocal Separation & Dereverberation +- [Music Source Separation Training](https://github.com/ZFTurbo/Music-Source-Separation-Training) +- [Lead Vocal Separation](https://huggingface.co/becruily/mel-band-roformer-karaoke) +- [Vocal Dereverberation](https://huggingface.co/anvuew/dereverb_mel_band_roformer) + +### 🎼 F0 Extraction +- [RMVPE](https://github.com/Dream-High/RMVPE) + +### 📝 Lyrics Transcription (ASR) +- [Paraformer](https://modelscope.cn/models/iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch) +- [Parakeet-tdt-0.6b-v2](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2) + +### 🎶 Note Transcription +- [ROSVOT](https://github.com/RickyL-2000/ROSVOT) + +We sincerely thank the authors of these repositories for their exceptional open-source contributions, which have been fundamental to the development of this toolkit. diff --git a/preprocess/pipeline.py b/preprocess/pipeline.py new file mode 100644 index 0000000..f3a69c7 --- /dev/null +++ b/preprocess/pipeline.py @@ -0,0 +1,146 @@ +import json +import shutil +import soundfile as sf +from pathlib import Path +import librosa + +from preprocess.utils import convert_metadata, merge_short_segments + +from preprocess.tools import ( + F0Extractor, + VocalDetector, + VocalSeparator, + NoteTranscriber, + LyricTranscriber, +) + + +class PreprocessPipeline: + def __init__(self, device: str, language: str, save_dir: str, vocal_sep: bool = True, max_merge_duration: int = 60000): + self.device = device + self.language = language + self.save_dir = save_dir + self.vocal_sep = vocal_sep + self.max_merge_duration = max_merge_duration + + if vocal_sep: + self.vocal_separator = VocalSeparator( + sep_model_path="pretrained_models/SoulX-Singer-Preprocess/mel-band-roformer-karaoke/mel_band_roformer_karaoke_becruily.ckpt", + sep_config_path="pretrained_models/SoulX-Singer-Preprocess/mel-band-roformer-karaoke/config_karaoke_becruily.yaml", + der_model_path="pretrained_models/SoulX-Singer-Preprocess/dereverb_mel_band_roformer/dereverb_mel_band_roformer_anvuew_sdr_19.1729.ckpt", + der_config_path="pretrained_models/SoulX-Singer-Preprocess/dereverb_mel_band_roformer/dereverb_mel_band_roformer_anvuew.yaml", + device=device + ) + else: + self.vocal_separator = None + self.f0_extractor = F0Extractor( + model_path="pretrained_models/SoulX-Singer-Preprocess/rmvpe/rmvpe.pt", + device=device, + ) + self.vocal_detector = VocalDetector( + cut_wavs_output_dir= f"{save_dir}/cut_wavs", + ) + self.lyric_transcriber = LyricTranscriber( + zh_model_path="pretrained_models/SoulX-Singer-Preprocess/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", + en_model_path="pretrained_models/SoulX-Singer-Preprocess/parakeet-tdt-0.6b-v2/parakeet-tdt-0.6b-v2.nemo", + device=device + ) + self.note_transcriber = NoteTranscriber( + rosvot_model_path="pretrained_models/SoulX-Singer-Preprocess/rosvot/rosvot/model.pt", + rwbd_model_path="pretrained_models/SoulX-Singer-Preprocess/rosvot/rwbd/model.pt", + device=device + ) + + def run( + self, + audio_path: str, + vocal_sep: bool = True, + max_merge_duration: int = 60000, + language: str = "Mandarin" + ) -> None: + vocal_sep = self.vocal_sep if vocal_sep is None else vocal_sep + max_merge_duration = self.max_merge_duration if max_merge_duration is None else max_merge_duration + language = self.language if language is None else language + output_dir = Path(self.save_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + if vocal_sep: + # Perform vocal/accompaniment separation + sep = self.vocal_separator.process(audio_path) + vocal = sep.vocals_dereverbed.T + acc = sep.accompaniment.T + sample_rate = sep.sample_rate + + vocal_path = output_dir / "vocal.wav" + acc_path = output_dir / "acc.wav" + sf.write(vocal_path, vocal, sample_rate) + sf.write(acc_path, acc, sample_rate) + else: + # Use the original audio as vocal source (no separation) + vocal, sample_rate = librosa.load(audio_path, sr=None, mono=True) + vocal_path = output_dir / "vocal.wav" + sf.write(vocal_path, vocal, sample_rate) + + vocal_f0 = self.f0_extractor.process(str(vocal_path)) + segments = self.vocal_detector.process(str(vocal_path), f0=vocal_f0) + + metadata = [] + for seg in segments: + self.f0_extractor.process(seg["wav_fn"], f0_path=seg["wav_fn"].replace(".wav", "_f0.npy")) + words, durs = self.lyric_transcriber.process( + seg["wav_fn"], language + ) + seg["words"] = words + seg["word_durs"] = durs + seg["language"] = language + metadata.append( + self.note_transcriber.process(seg, segment_info=seg) + ) + + merged = merge_short_segments( + vocal, + sample_rate, + metadata, + output_dir / "long_cut_wavs", + max_duration_ms=max_merge_duration, + ) + + final_metadata = [] + + for item in merged: + self.f0_extractor.process(item.wav_fn, f0_path=item.wav_fn.replace(".wav", "_f0.npy")) + final_metadata.append(convert_metadata(item)) + + with open(output_dir / "metadata.json", "w", encoding="utf-8") as f: + json.dump(final_metadata, f, ensure_ascii=False, indent=2) + + shutil.copy(output_dir / "metadata.json", audio_path.replace(".wav", ".json").replace(".mp3", ".json").replace(".flac", ".json")) + + +def main(args): + pipeline = PreprocessPipeline( + device=args.device, + language=args.language, + save_dir=args.save_dir, + vocal_sep=args.vocal_sep, + max_merge_duration=args.max_merge_duration, + ) + pipeline.run( + audio_path=args.audio_path, + language=args.language + ) + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument("--audio_path", type=str, required=True, help="Path to the input audio file") + parser.add_argument("--save_dir", type=str, required=True, help="Directory to save the output files") + parser.add_argument("--language", type=str, default="Mandarin", help="Language of the audio") + parser.add_argument("--device", type=str, default="cuda:0", help="Device to run the models on") + parser.add_argument("--vocal_sep", type=bool, default=True, help="Whether to perform vocal separation") + parser.add_argument("--max_merge_duration", type=int, default=60000, help="Maximum merged segment duration in milliseconds") + args = parser.parse_args() + + main(args) diff --git a/preprocess/tools/__init__.py b/preprocess/tools/__init__.py new file mode 100644 index 0000000..4bacfc0 --- /dev/null +++ b/preprocess/tools/__init__.py @@ -0,0 +1,53 @@ +"""Preprocess tools. + +This package provides a thin, stable import surface for common preprocess components. + +Examples: + from preprocess.tools import ( + F0Extractor, + PitchExtractor, + VocalDetectionModel, + VocalSeparationModel, + VocalExtractionModel, + NoteTranscriptionModel, + LyricTranscriptionModel, + ) + +Note: + Keep these imports lightweight. If a tool pulls heavy dependencies at import time, + consider switching to lazy imports. +""" + +from __future__ import annotations + +# Core tools +from .f0_extraction import F0Extractor +from .vocal_detection import VocalDetector + +# Some tools may live outside this package in different layouts across branches. +# Keep the public surface stable while avoiding hard import failures. +try: + from .vocal_separation.model import VocalSeparator # type: ignore +except Exception: # pragma: no cover + VocalSeparator = None # type: ignore + +try: + from .note_transcription.model import NoteTranscriber # type: ignore +except Exception: # pragma: no cover + NoteTranscriber = None # type: ignore +try: + from .lyric_transcription import LyricTranscriber +except Exception: # pragma: no cover + LyricTranscriber = None # type: ignore + +__all__ = [ + "F0Extractor", + "VocalDetector", +] + +if VocalSeparator is not None: + __all__.append("VocalSeparator") +if LyricTranscriber is not None: + __all__.append("LyricTranscriber") +if NoteTranscriber is not None: + __all__.append("NoteTranscriber") diff --git a/preprocess/tools/f0_extraction.py b/preprocess/tools/f0_extraction.py new file mode 100644 index 0000000..5ec2cf7 --- /dev/null +++ b/preprocess/tools/f0_extraction.py @@ -0,0 +1,527 @@ +# https://github.com/Dream-High/RMVPE +import math +import time +import librosa +import numpy as np +from librosa.filters import mel +from scipy.interpolate import interp1d + +from typing import Optional + +import torch +import torch.nn as nn +import torch.nn.functional as F + + +class BiGRU(nn.Module): + def __init__(self, input_features, hidden_features, num_layers): + super(BiGRU, self).__init__() + self.gru = nn.GRU( + input_features, + hidden_features, + num_layers=num_layers, + batch_first=True, + bidirectional=True, + ) + + def forward(self, x): + return self.gru(x)[0] + + +class ConvBlockRes(nn.Module): + def __init__(self, in_channels, out_channels, momentum=0.01): + super(ConvBlockRes, self).__init__() + self.conv = nn.Sequential( + nn.Conv2d( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + bias=False, + ), + nn.BatchNorm2d(out_channels, momentum=momentum), + nn.ReLU(), + nn.Conv2d( + in_channels=out_channels, + out_channels=out_channels, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + bias=False, + ), + nn.BatchNorm2d(out_channels, momentum=momentum), + nn.ReLU(), + ) + if in_channels != out_channels: + self.shortcut = nn.Conv2d(in_channels, out_channels, (1, 1)) + + def forward(self, x): + if not hasattr(self, "shortcut"): + return self.conv(x) + x + else: + return self.conv(x) + self.shortcut(x) + + +class ResEncoderBlock(nn.Module): + def __init__(self, in_channels, out_channels, kernel_size, n_blocks=1, momentum=0.01): + super(ResEncoderBlock, self).__init__() + self.n_blocks = n_blocks + self.conv = nn.ModuleList() + self.conv.append(ConvBlockRes(in_channels, out_channels, momentum)) + for i in range(n_blocks - 1): + self.conv.append(ConvBlockRes(out_channels, out_channels, momentum)) + self.kernel_size = kernel_size + if self.kernel_size is not None: + self.pool = nn.AvgPool2d(kernel_size=kernel_size) + + def forward(self, x): + for conv in self.conv: + x = conv(x) + if self.kernel_size is not None: + return x, self.pool(x) + else: + return x + + +class Encoder(nn.Module): + def __init__(self, in_channels, in_size, n_encoders, kernel_size, n_blocks, out_channels=16, momentum=0.01): + super(Encoder, self).__init__() + self.n_encoders = n_encoders + self.bn = nn.BatchNorm2d(in_channels, momentum=momentum) + self.layers = nn.ModuleList() + self.latent_channels = [] + for i in range(self.n_encoders): + self.layers.append( + ResEncoderBlock(in_channels, out_channels, kernel_size, n_blocks, momentum=momentum) + ) + self.latent_channels.append([out_channels, in_size]) + in_channels = out_channels + out_channels *= 2 + in_size //= 2 + self.out_size = in_size + self.out_channel = out_channels + + def forward(self, x): + concat_tensors = [] + x = self.bn(x) + for layer in self.layers: + t, x = layer(x) + concat_tensors.append(t) + return x, concat_tensors + + +class Intermediate(nn.Module): + def __init__(self, in_channels, out_channels, n_inters, n_blocks, momentum=0.01): + super(Intermediate, self).__init__() + self.n_inters = n_inters + self.layers = nn.ModuleList() + self.layers.append(ResEncoderBlock(in_channels, out_channels, None, n_blocks, momentum)) + for i in range(self.n_inters - 1): + self.layers.append(ResEncoderBlock(out_channels, out_channels, None, n_blocks, momentum)) + + def forward(self, x): + for layer in self.layers: + x = layer(x) + return x + + +class ResDecoderBlock(nn.Module): + def __init__(self, in_channels, out_channels, stride, n_blocks=1, momentum=0.01): + super(ResDecoderBlock, self).__init__() + out_padding = (0, 1) if stride == (1, 2) else (1, 1) + self.n_blocks = n_blocks + self.conv1 = nn.Sequential( + nn.ConvTranspose2d( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=(3, 3), + stride=stride, + padding=(1, 1), + output_padding=out_padding, + bias=False, + ), + nn.BatchNorm2d(out_channels, momentum=momentum), + nn.ReLU(), + ) + self.conv2 = nn.ModuleList() + self.conv2.append(ConvBlockRes(out_channels * 2, out_channels, momentum)) + for i in range(n_blocks - 1): + self.conv2.append(ConvBlockRes(out_channels, out_channels, momentum)) + + def forward(self, x, concat_tensor): + x = self.conv1(x) + x = torch.cat((x, concat_tensor), dim=1) + for conv2 in self.conv2: + x = conv2(x) + return x + + +class Decoder(nn.Module): + def __init__(self, in_channels, n_decoders, stride, n_blocks, momentum=0.01): + super(Decoder, self).__init__() + self.layers = nn.ModuleList() + self.n_decoders = n_decoders + for i in range(self.n_decoders): + out_channels = in_channels // 2 + self.layers.append( + ResDecoderBlock(in_channels, out_channels, stride, n_blocks, momentum) + ) + in_channels = out_channels + + def forward(self, x, concat_tensors): + for i, layer in enumerate(self.layers): + x = layer(x, concat_tensors[-1 - i]) + return x + + +class DeepUnet(nn.Module): + def __init__(self, kernel_size, n_blocks, en_de_layers=5, inter_layers=4, in_channels=1, en_out_channels=16): + super(DeepUnet, self).__init__() + self.encoder = Encoder(in_channels, 128, en_de_layers, kernel_size, n_blocks, en_out_channels) + self.intermediate = Intermediate( + self.encoder.out_channel // 2, + self.encoder.out_channel, + inter_layers, + n_blocks, + ) + self.decoder = Decoder(self.encoder.out_channel, en_de_layers, kernel_size, n_blocks) + + def forward(self, x): + x, concat_tensors = self.encoder(x) + x = self.intermediate(x) + x = self.decoder(x, concat_tensors) + return x + + +class E2E(nn.Module): + def __init__(self, n_blocks, n_gru, kernel_size, en_de_layers=5, inter_layers=4, in_channels=1, en_out_channels=16): + super(E2E, self).__init__() + self.unet = DeepUnet(kernel_size, n_blocks, en_de_layers, inter_layers, in_channels, en_out_channels) + self.cnn = nn.Conv2d(en_out_channels, 3, (3, 3), padding=(1, 1)) + if n_gru: + self.fc = nn.Sequential( + BiGRU(3 * 128, 256, n_gru), + nn.Linear(512, 360), + nn.Dropout(0.25), + nn.Sigmoid(), + ) + else: + self.fc = nn.Sequential( + nn.Linear(3 * 128, 360), + nn.Dropout(0.25), + nn.Sigmoid() + ) + + def forward(self, mel): + mel = mel.transpose(-1, -2).unsqueeze(1) + x = self.cnn(self.unet(mel)).transpose(1, 2).flatten(-2) + x = self.fc(x) + return x + + + +class MelSpectrogram(torch.nn.Module): + def __init__(self, is_half, n_mel_channels, sampling_rate, win_length, hop_length, + n_fft=None, mel_fmin=0, mel_fmax=None, clamp=1e-5): + super().__init__() + n_fft = win_length if n_fft is None else n_fft + self.hann_window = {} + mel_basis = mel( + sr=sampling_rate, + n_fft=n_fft, + n_mels=n_mel_channels, + fmin=mel_fmin, + fmax=mel_fmax, + htk=True, + ) + mel_basis = torch.from_numpy(mel_basis).float() + self.register_buffer("mel_basis", mel_basis) + self.n_fft = win_length if n_fft is None else n_fft + self.hop_length = hop_length + self.win_length = win_length + self.sampling_rate = sampling_rate + self.n_mel_channels = n_mel_channels + self.clamp = clamp + self.is_half = is_half + + def forward(self, audio, keyshift=0, speed=1, center=True): + factor = 2 ** (keyshift / 12) + n_fft_new = int(np.round(self.n_fft * factor)) + win_length_new = int(np.round(self.win_length * factor)) + hop_length_new = int(np.round(self.hop_length * speed)) + + keyshift_key = str(keyshift) + "_" + str(audio.device) + if keyshift_key not in self.hann_window: + self.hann_window[keyshift_key] = torch.hann_window(win_length_new).to(audio.device) + + fft = torch.stft( + audio, + n_fft=n_fft_new, + hop_length=hop_length_new, + win_length=win_length_new, + window=self.hann_window[keyshift_key], + center=center, + return_complex=True, + ) + magnitude = torch.sqrt(fft.real.pow(2) + fft.imag.pow(2)) + + if keyshift != 0: + size = self.n_fft // 2 + 1 + resize = magnitude.size(1) + if resize < size: + magnitude = F.pad(magnitude, (0, 0, 0, size - resize)) + magnitude = magnitude[:, :size, :] * self.win_length / win_length_new + + mel_output = torch.matmul(self.mel_basis, magnitude) + if self.is_half: + mel_output = mel_output.half() + log_mel_spec = torch.log(torch.clamp(mel_output, min=self.clamp)) + return log_mel_spec + + + +class RMVPE: + def __init__(self, model_path: str, is_half, device=None): + self.is_half = is_half + if device is None: + device = "cuda:0" if torch.cuda.is_available() else "cpu" + self.device = torch.device(device) if isinstance(device, str) else device + + self.mel_extractor = MelSpectrogram( + is_half=is_half, + n_mel_channels=128, + sampling_rate=16000, + win_length=1024, + hop_length=160, + n_fft=None, + mel_fmin=30, + mel_fmax=8000 + ).to(self.device) + + model = E2E(n_blocks=4, n_gru=1, kernel_size=(2, 2)) + ckpt = torch.load(model_path, map_location=self.device) + model.load_state_dict(ckpt) + model.eval() + + if is_half: + model = model.half() + else: + model = model.float() + + self.model = model.to(self.device) + + cents_mapping = 20 * np.arange(360) + 1997.3794084376191 + self.cents_mapping = np.pad(cents_mapping, (4, 4)) # 368 + + def mel2hidden(self, mel): + with torch.no_grad(): + n_frames = mel.shape[-1] + n_pad = 32 * ((n_frames - 1) // 32 + 1) - n_frames + if n_pad > 0: + mel = F.pad(mel, (0, n_pad), mode="constant") + mel = mel.half() if self.is_half else mel.float() + hidden = self.model(mel) + return hidden[:, :n_frames] + + def decode(self, hidden, thred=0.03): + cents_pred = self.to_local_average_cents(hidden, thred=thred) + f0 = 10 * (2 ** (cents_pred / 1200)) + f0[f0 == 10] = 0 + return f0 + + def infer_from_audio(self, audio, thred=0.03): + if not torch.is_tensor(audio): + audio = torch.from_numpy(audio) + + mel = self.mel_extractor(audio.float().to(self.device).unsqueeze(0), center=True) + hidden = self.mel2hidden(mel) + hidden = hidden.squeeze(0).cpu().numpy() + + if self.is_half: + hidden = hidden.astype("float32") + + f0 = self.decode(hidden, thred=thred) + return f0 + + def to_local_average_cents(self, salience, thred=0.05): + center = np.argmax(salience, axis=1) + salience = np.pad(salience, ((0, 0), (4, 4))) + center += 4 + + todo_salience = [] + todo_cents_mapping = [] + starts = center - 4 + ends = center + 5 + + for idx in range(salience.shape[0]): + todo_salience.append(salience[:, starts[idx]:ends[idx]][idx]) + todo_cents_mapping.append(self.cents_mapping[starts[idx]:ends[idx]]) + + todo_salience = np.array(todo_salience) + todo_cents_mapping = np.array(todo_cents_mapping) + product_sum = np.sum(todo_salience * todo_cents_mapping, 1) + weight_sum = np.sum(todo_salience, 1) + devided = product_sum / weight_sum + + maxx = np.max(salience, axis=1) + devided[maxx <= thred] = 0 + + return devided + +class F0Extractor: + """Extract frame-level f0 from singing voice. + + Wrapper around an RMVPE network that: + 1) loads the checkpoint once in ``__init__`` + 2) exposes a simple :py:meth:`process` API and optionally saves ``*_f0.npy``. + """ + def __init__( + self, + model_path: str, + device: str = "cpu", + *, + is_half: bool = False, + input_sr: int = 16000, + target_sr: int = 24000, + hop_size: int = 480, + max_duration: float = 300, + thred: float = 0.03, + verbose: bool = True, + ): + """Initialize the f0 extractor. + + Args: + model_path: Path to RMVPE checkpoint. + device: Torch device string, e.g. ``"cuda:0"`` / ``"cpu"``. + is_half: Whether to run the model in fp16. + input_sr: Input resample rate used by RMVPE frontend. + target_sr: Target sample rate for the output f0 grid. + hop_size: Target hop size for the output f0 grid. + max_duration: Max duration (seconds) for interpolation grid. + thred: Voicing threshold used when decoding salience. + verbose: Whether to print verbose logs. + """ + self.model_path = model_path + self.input_sr = input_sr + self.target_sr = target_sr + self.hop_size = hop_size + self.max_duration = max_duration + self.thred = thred + + self.verbose = verbose + + self.model = RMVPE(model_path, is_half=is_half, device=device) + + if self.verbose: + print( + "[f0 extraction] init success:", + f"device={device}", + f"model_path={model_path}", + f"is_half={is_half}", + f"input_sr={input_sr}", + f"target_sr={target_sr}", + f"hop_size={hop_size}", + f"thred={thred}", + ) + + @staticmethod + def interpolate_f0( + f0_16k: np.ndarray, + original_length: int, + original_sr: int, + *, + target_sr: int = 48000, + hop_size: int = 256, + max_duration: float = 20.0, + ) -> np.ndarray: + """Interpolate f0 from RMVPE's 16k hop grid to target mel hop grid.""" + mel_target_sr = target_sr + mel_hop_size = hop_size + mel_max_duration = max_duration + + batch_max_length = int(mel_max_duration * mel_target_sr / mel_hop_size) + duration_in_seconds = original_length / original_sr + effective_target_length = int(duration_in_seconds * mel_target_sr) + original_frames = math.ceil(effective_target_length / mel_hop_size) + target_frames = min(original_frames, batch_max_length) + + rmvpe_hop = 160 + t_16k = np.arange(len(f0_16k)) * (rmvpe_hop / 16000.0) + t_target = np.arange(target_frames) * (mel_hop_size / float(mel_target_sr)) + + if len(f0_16k) > 0: + f_interp = interp1d( + t_16k, + f0_16k, + kind="linear", + bounds_error=False, + fill_value=0.0, + assume_sorted=True, + ) + f0 = f_interp(t_target) + else: + f0 = np.zeros(target_frames) + + if len(f0) != target_frames: + f0 = ( + f0[:target_frames] + if len(f0) > target_frames + else np.pad(f0, (0, target_frames - len(f0)), "constant") + ) + + return f0 + + def process(self, audio_path: str, *, f0_path: str | None = None, verbose: Optional[bool] = None) -> np.ndarray: + """Run f0 extraction for a single wav. + + Args: + audio_path: Path to the input wav file. + f0_path: if is not None, save the f0 data to this path. + verbose: Override instance-level verbose flag for this call. + + Returns: + np.ndarray: shape ``[T]``, f0 in Hz (0 for unvoiced). + """ + verbose = self.verbose if verbose is None else verbose + if verbose: + print(f"[f0 extraction] process: start: {audio_path}") + t0 = time.time() + + audio, _ = librosa.load(audio_path, sr=self.input_sr) + f0_16k = self.model.infer_from_audio(audio, thred=self.thred) + f0 = self.interpolate_f0( + f0_16k, + original_length=audio.shape[-1], + original_sr=self.input_sr, + target_sr=self.target_sr, + hop_size=self.hop_size, + max_duration=self.max_duration, + ) + + if verbose: + dt = time.time() - t0 + voiced_ratio = float(np.mean(f0 > 0)) if len(f0) else 0.0 + print( + "[f0 extraction] process: done:", + f"frames={len(f0)}", + f"voiced_ratio={voiced_ratio:.3f}", + f"time={dt:.3f}s", + ) + if f0_path is not None: + np.save(f0_path, f0) + + return f0 + + +if __name__ == "__main__": + model_path = ( + "pretrained_models/rmvpe/rmvpe.pt" + ) + audio_path = "./outputs/transcription/test.wav" + + pe = F0Extractor( + model_path, + device="cuda", + ) + f0 = pe.process(audio_path) diff --git a/preprocess/tools/g2p.py b/preprocess/tools/g2p.py new file mode 100644 index 0000000..5861d06 --- /dev/null +++ b/preprocess/tools/g2p.py @@ -0,0 +1,72 @@ +import re + +import ToJyutping +from g2pM import G2pM +from g2p_en import G2p as G2pE + +_EN_WORD_RE = re.compile(r"^[A-Za-z]+(?:'[A-Za-z]+)*$") +_ZH_WORD_RE = re.compile(r"[\u4e00-\u9fff]") + +EN_FLAG = "en_" +YUE_FLAG = "yue_" +ZH_FLAG = "zh_" + +g2p_zh = G2pM() +g2p_en = G2pE() + + +def is_chinese_char(word: str) -> bool: + if len(word) != 1: + return False + return bool(_ZH_WORD_RE.fullmatch(word)) + +def is_english_word(word: str) -> bool: + if not word: + return False + return bool(_EN_WORD_RE.fullmatch(word)) + +def g2p_cantonese(sent): + return ToJyutping.get_jyutping_list(sent) # with tone + +def g2p_mandarin(sent): + return g2p_zh(sent, tone=True, char_split=False) + +def g2p_english(word): + return g2p_en(word) + +def g2p_transform(words, lang): + + zh_words = [] + transformed_words = [0] * len(words) + + for idx, w in enumerate(words): + if w == "": + transformed_words[idx] = w + continue + + w = w.replace("?", "").replace(".", "").replace("!", "").replace(",", "") + + if is_chinese_char(w): + zh_words.append([idx, w]) + else: + if is_english_word(w): + w = EN_FLAG + "-".join(g2p_english(w.lower())) + else: + w = "" + transformed_words[idx] = w + + sent = "".join([k[1] for k in zh_words]) + + # zh (zh and yue) transformer to g2p + if len(sent) > 0: + if lang == "Cantonese": + g2pm_rst = g2p_cantonese(sent) # with tone + g2pm_rst = [YUE_FLAG + k[1] for k in g2pm_rst] + else: + g2pm_rst = g2p_mandarin(sent) + g2pm_rst = [ZH_FLAG + k for k in g2pm_rst] + for p, w in zip([k[0] for k in zh_words], g2pm_rst): + transformed_words[p] = w + + return transformed_words + diff --git a/preprocess/tools/lyric_transcription.py b/preprocess/tools/lyric_transcription.py new file mode 100644 index 0000000..a0b5d2d --- /dev/null +++ b/preprocess/tools/lyric_transcription.py @@ -0,0 +1,279 @@ +# https://modelscope.cn/models/iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary +# https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2 +import os +import re +import time +from typing import Any, Dict, List, Tuple + +import librosa +import numpy as np +from funasr import AutoModel + + +def _build_words_with_gaps(raw_words, raw_timestamps, wav_fn: str): + words, word_durs = [], [] + prev = 0.0 + for w, t in zip(raw_words, raw_timestamps): + s, e = float(t[0]), float(t[1]) + if s > prev: + words.append("") + word_durs.append(s - prev) + words.append(w) + word_durs.append(e - s) + prev = e + + wav_len = librosa.get_duration(filename=wav_fn) + if wav_len > prev: + if len(words) == 0: + words.append("") + word_durs.append(wav_len) + return words, word_durs + if words[-1] != "": + words.append("") + word_durs.append(wav_len - prev) + else: + word_durs[-1] += wav_len - prev + + return words, word_durs + +def _word_dur_post_process(words, word_durs, f0): + """Post-process word durations using f0 to better place silences. + """ + # f0 time grid parameters + sr = 24000 # f0 sample rate + hop_length = 480 # f0 hop length + + # Convert word durations (seconds) to frame boundaries on the f0 grid. + boundaries = np.cumsum([ + 0, + *[ + int(dur * sr / hop_length) + for dur in word_durs + ], + ]).tolist() + + sil_tolerance = 5 # tolerance frames for silence detection + ext_tolerance = 5 # tolerance frames for vocal extension + + new_words: list[str] = [] + new_word_durs: list[float] = [] + if words: + new_words.append(words[0]) + new_word_durs.append(word_durs[0]) + + for i in range(1, len(words)): + word = words[i] + if word == "": + start_frame = boundaries[i] + end_frame = boundaries[i + 1] + + num_frames = end_frame - start_frame + frame_idx = start_frame + + # Find first region with at least 5 consecutive "unvoiced" frames. + unvoiced_count = 0 + while frame_idx < end_frame: + if f0[frame_idx] <= 1: # unvoiced + unvoiced_count += 1 + if unvoiced_count >= sil_tolerance: + frame_idx -= sil_tolerance - 1 # back to the last voiced frame + break + else: + unvoiced_count = 0 + frame_idx += 1 + + voice_frames = frame_idx - start_frame + + if voice_frames >= int(num_frames * 0.9): # over 90% voiced + # Treat the whole "" as silence and merge into previous word. + new_word_durs[-1] += word_durs[i] + elif voice_frames >= ext_tolerance: # over 5 frames voiced + # Split the "" into two parts: leading silence and tail kept as "". + dur = voice_frames * hop_length / sr + new_word_durs[-1] += dur + new_words.append("") + new_word_durs.append(word_durs[i] - dur) + else: + # Too short to adjust, keep as-is. + new_words.append(word) + new_word_durs.append(word_durs[i]) + else: + new_words.append(word) + new_word_durs.append(word_durs[i]) + + return new_words, new_word_durs + + +class _ASRZhModel: + """Mandarin/Cantonese ASR wrapper.""" + + def __init__(self, model_path: str, device: str): + self.model = AutoModel( + model=model_path, + disable_update=True, + device=device, + ) + + def process(self, wav_fn): + out = self.model.generate(wav_fn, output_timestamp=True)[0] + raw_words = out["text"].replace("@", "").split(" ") + raw_timestamps = [[t[0] / 1000, t[1] / 1000] for t in out["timestamp"]] + words, word_durs = _build_words_with_gaps(raw_words, raw_timestamps, wav_fn) + + if os.path.exists(wav_fn.replace(".wav", "_f0.npy")): + words, word_durs = _word_dur_post_process( + words, word_durs, np.load(wav_fn.replace(".wav", "_f0.npy")) + ) + + return words, word_durs + + +class _ASREnModel: + """English ASR wrapper for NeMo Parakeet-TDT.""" + + def __init__(self, model_path: str, device: str): + try: + import nemo.collections.asr as nemo_asr # type: ignore + except Exception as e: # pragma: no cover + raise ImportError( + "NeMo (nemo_toolkit) is required for ASR English but is not available in this Python env. " + "Install it in the active environment, then retry." + ) from e + + self.model = nemo_asr.models.ASRModel.restore_from( + restore_path=model_path, + map_location=device, + ) + self.model.eval() + + @staticmethod + def _clean_word(word: str) -> str: + return re.sub(r"[\?\.,:]", "", word).strip() + + @staticmethod + def _extract_word_segments(output: Any) -> List[Dict[str, Any]]: + ts = getattr(output, "timestamp", None) + if not ts or not isinstance(ts, dict): + return [] + word_ts = ts.get("word") + return word_ts if isinstance(word_ts, list) else [] + + def process(self, wav_fn: str) -> Tuple[List[str], List[float]]: + outputs = self.model.transcribe( + [wav_fn], + timestamps=True, + batch_size=1, + num_workers=0, + ) + output = outputs[0] if outputs else None + + raw_words: List[str] = [] + raw_timestamps: List[List[float]] = [] + if output is not None: + for w in self._extract_word_segments(output): + s, e = float(w.get("start", 0.0)), float(w.get("end", 0.0)) + word = self._clean_word(str(w.get("word", ""))) + if word: + raw_words.append(word) + raw_timestamps.append([s, e]) + + words, durs = _build_words_with_gaps(raw_words, raw_timestamps, wav_fn) + + if os.path.exists(wav_fn.replace(".wav", "_f0.npy")): + words, durs = _word_dur_post_process( + words, durs, np.load(wav_fn.replace(".wav", "_f0.npy")) + ) + + return words, durs + + +class LyricTranscriber: + """Transcribe lyrics from singing voice segment + """ + + def __init__( + self, + zh_model_path: str, + en_model_path: str, + device: str = "cuda", + *, + verbose: bool = True, + ): + """Initialize lyric transcriber. + + Args: + zh_model_path (str): Path to the Chinese model file. + en_model_path (str): Path to the English model file. + device (str): Device to use for tensor operations. + verbose (bool): Whether to print verbose logs. + """ + self.verbose = verbose + self.device = device + self.zh_model_path = zh_model_path + self.en_model_path = en_model_path + + if self.verbose: + print( + "[lyric transcription] init: start:", + f"device={device}", + f"model_path={zh_model_path}", + ) + + # Always initialize Chinese ASR. + self.zh_model = _ASRZhModel(device=device, model_path=zh_model_path) + + # English ASR will be lazily initialized on first English request to avoid long waiting cost when importing NeMo + self.en_model = None + + if self.verbose: + print("[lyric transcription] init: success") + + def process(self, wav_fn, language: str | None = "Mandarin", *, verbose: bool | None = None): + """ Lyric transcriber process + + Args: + wav_fn (str): Path to the audio file. + language (str | None): Language of the audio. Defaults to "Mandarin". Supports "Mandarin", "Cantonese" and "English". + verbose (bool | None): Whether to print verbose logs. Defaults to None. + """ + v = self.verbose if verbose is None else verbose + if language not in {"Mandarin", "Cantonese", "English"}: + raise ValueError(f"Unsupported language: {language}, should be one of ['Mandarin', 'Cantonese', 'English']") + if v: + print(f"[lyric transcription] process: start: wav_fn={wav_fn} language={language}") + t0 = time.time() + + lang = (language or "auto").lower() + if lang in {"english"}: + if self.en_model is None: + # Lazy-load NeMo model only when English is actually used. + if v: + print("[lyric transcription] init English ASR, please make sure NeMo is installed") + self.en_model = _ASREnModel(model_path=self.en_model_path, device=self.device) + out = self.en_model.process(wav_fn) + else: + out = self.zh_model.process(wav_fn) + + if v: + words, durs = out + n_words = len(words) if isinstance(words, list) else 0 + dur_sum = float(sum(durs)) if isinstance(durs, list) else 0.0 + dt = time.time() - t0 + print( + "[lyric transcription] process: done:", + f"n_words={n_words}", + f"dur_sum={dur_sum:.3f}s", + f"time={dt:.3f}s", + ) + + return out + + +if __name__ == "__main__": + m = LyricTranscriber( + zh_model_path="pretrained_models/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", + en_model_path="pretrained_models/parakeet-tdt-0.6b-v2/parakeet-tdt-0.6b-v2.nemo", + device="cuda" + ) + print(m.process("example/test/asr_zh.wav", language="Mandarin")) + print(m.process("example/test/asr_en.wav", language="English")) \ No newline at end of file diff --git a/preprocess/tools/midi_editor/README.md b/preprocess/tools/midi_editor/README.md new file mode 100644 index 0000000..88dfb26 --- /dev/null +++ b/preprocess/tools/midi_editor/README.md @@ -0,0 +1,173 @@ +# 🎹 MIDI Editor - Web-based Singing MIDI Editor + +[English](README.md) | [简体中文](README_CN.md) + +A full-featured web MIDI editor for singing voice production, similar to ACE-Studio and VOCALOID. It supports real-time drag editing of MIDI notes, lyric editing, audio waveform alignment, and importing/exporting MIDI files with lyrics. + +![MIDI Editor](https://img.shields.io/badge/React-19.2-blue) ![TypeScript](https://img.shields.io/badge/TypeScript-5.9-blue) ![Vite](https://img.shields.io/badge/Vite-7.2-purple) + +## ✨ Features + +### 🎼 Piano Roll Editing + +- **Visual note editing**: Full range from C1 to C8 with intuitive piano keys +- **Drag operations**: + - Move notes: drag note blocks to adjust position and pitch + - Resize start: drag the left edge to adjust start time + - Resize end: drag the right edge to adjust end time +- **Double-click to add**: Add new notes quickly in empty areas +- **Piano key preview**: Click a key to audition the pitch + +### 🔍 Zoom & Navigation + +- **Horizontal zoom** +- **Vertical zoom** +- **Dynamic snapping**: finer snap granularity at higher zoom (min 0.01s) +- **Auto scroll**: keep the playhead visible during playback + +### 📝 Lyric Editing + +- **Inline editing**: edit lyrics for each note in the side list +- **Batch fill**: enter a string and auto-fill notes in order +- **Fill from selection**: start batch fill from the selected note +- **Precise fields**: edit PITCH, START, and END directly +- **Confirm edits**: press Enter or click ✓ to confirm + +### 🎵 Audio Alignment + +- **Waveform display**: sync waveform with the MIDI timeline +- **Formats**: MP3, WAV, OGG, FLAC, M4A, AAC +- **Sync playback**: play audio and MIDI together with independent mute +- **Click to seek**: click waveform or timeline to seek + +### ⚠️ Overlap Detection + +- **Visual highlight**: overlapping notes blink in red +- **Smart tolerance**: adjacent notes (end equals next start) are not overlaps +- **One-click fix**: remove all overlaps automatically +- **Export warning**: warn if overlaps exist during export + +### 📥 Import & Export + +- **MIDI import**: parse standard MIDI and lyric metadata +- **MIDI export**: export MIDI with lyrics +- **Chinese support**: full UTF-8 lyrics support + +### 🎨 UI & UX + +- **Theme toggle**: light and dark modes +- **Responsive layout**: adapts to window size +- **SVG grid**: cross-browser grid rendering +- **Status feedback**: real-time state and error tips + +## 🚀 Quick Start + +### Requirements + +- Node.js 18+ +- npm or yarn + +### Install + +```bash +# Clone +git clone +cd MIDI_Editor + +# Install dependencies +npm install + +# Start dev server +npm run dev + +# Expose to LAN +npm run dev -- --host 0.0.0.0 +``` + +### Build + +```bash +# Build for production +npm run build + +# Preview build +npm run preview +``` + +## 📖 Usage + +### Basic Workflow + +1. **Import MIDI**: click Import MIDI and select a .mid file +2. **Edit notes**: drag notes in the piano roll to adjust time and pitch +3. **Add lyrics**: edit lyrics in the right-side list +4. **Align audio** (optional): import reference audio +5. **Export**: click Export MIDI with lyrics + +### Shortcuts + +| Action | Description | +|------|------| +| Double-click piano roll | Add a new note | +| Double-click note | Edit lyric | +| Drag note | Move note and pitch | +| Drag note edges | Resize note | +| Backspace / Delete | Delete selected note | +| Enter | Confirm value edits | +| Escape | Cancel value edits | +| Ctrl(Command) + Wheel | Horizontal zoom | +| Ctrl(Command) + Shift(Option) + Wheel | Vertical zoom | + +### Playback Controls + +| Button | Description | +|------|------| +| ⏮ | Go to start | +| ⏪ 2s | Back 2 seconds | +| ▶ / ⏸ | Play / Pause | +| 2s ⏩ | Forward 2 seconds | +| ⏭ | Go to end | + +## 🛠 Tech Stack + +- **Frontend**: React 19 + TypeScript +- **Build**: Vite 7 +- **State**: Zustand +- **Audio**: Tone.js +- **Waveform**: WaveSurfer.js +- **MIDI**: @tonejs/midi +- **Styles**: CSS with custom variables + +## 📁 Project Structure + +``` +. +├── eslint.config.js +├── index.html +├── package.json +├── postcss.config.js +├── README.md +├── README_CN.md +├── tailwind.config.js +├── tsconfig.app.json +├── tsconfig.json +├── tsconfig.node.json +├── vite.config.ts +├── public/ +└── src/ + ├── App.css + ├── App.tsx + ├── constants.ts + ├── index.css + ├── main.tsx + ├── types.ts + ├── assets/ + ├── components/ + │ ├── AudioTrack.tsx + │ ├── LyricTable.tsx + │ └── PianoRoll.tsx + ├── lib/ + │ └── midi.ts + └── store/ + └── useMidiStore.ts +``` \ No newline at end of file diff --git a/preprocess/tools/midi_editor/README_CN.md b/preprocess/tools/midi_editor/README_CN.md new file mode 100644 index 0000000..2b86851 --- /dev/null +++ b/preprocess/tools/midi_editor/README_CN.md @@ -0,0 +1,173 @@ +# 🎹 MIDI Editor - 网页端歌声 MIDI 编辑器 + +[English](README.md) | [简体中文](README_CN.md) + +一个功能完整的网页端歌声 MIDI 文件编辑器，类似 ACE-Studio 和 VOCALOID。支持实时拖拽调整 MIDI 音符、歌词编辑、音频波形对齐，以及导入导出含歌词的 MIDI 文件。 + +![MIDI Editor](https://img.shields.io/badge/React-19.2-blue) ![TypeScript](https://img.shields.io/badge/TypeScript-5.9-blue) ![Vite](https://img.shields.io/badge/Vite-7.2-purple) + +## ✨ 功能特性 + +### 🎼 钢琴卷帘编辑 + +- **可视化音符编辑**：支持 C1-C8 全音域显示，直观的钢琴键布局 +- **拖拽操作**： + - 移动音符：拖拽音符块调整位置和音高 + - 调整音头：拖拽音符左边缘调整开始时间 + - 调整音尾：拖拽音符右边缘调整结束时间 +- **双击添加**：在钢琴卷帘空白处双击快速添加新音符 +- **钢琴键试听**：点击左侧钢琴键可试听对应音高 + +### 🔍 缩放与导航 + +- **水平缩放** +- **垂直缩放** +- **动态精度**：缩放越大，音符调整的 snap 粒度越精细（最小 0.01 秒） +- **自动滚动**：播放时播放头自动保持可见 + +### 📝 歌词编辑 + +- **实时编辑**：右侧列表直接编辑每个音符的歌词 +- **批量填充**：输入一段歌词，按字顺序自动填充到音符 +- **从选中开始**：批量填充可从当前选中的音符开始 +- **精确调整**：可直接编辑 PITCH（音高）、START（开始时间）、END（结束时间） +- **确认机制**：修改数值后按 Enter 或点击 ✓ 确认，避免误操作 + +### 🎵 音频对齐 + +- **波形显示**：导入音频后显示波形，与 MIDI 同步滚动 +- **格式支持**：MP3、WAV、OGG、FLAC、M4A、AAC +- **同步播放**：音频与 MIDI 同步播放，可分别静音 +- **点击定位**：点击波形或时间尺可快速定位播放位置 + +### ⚠️ 重叠检测 + +- **可视化标注**：时间重叠的音符显示为红色并闪烁 +- **智能容差**：紧邻的音符（上一个结束 = 下一个开始）不视为重叠 +- **一键修复**：点击消除重叠按钮自动修复所有重叠 +- **导出提醒**：导出时如有重叠会弹出警告 + +### 📥 导入导出 + +- **MIDI 导入**：支持标准 MIDI 文件，自动解析歌词元数据 +- **MIDI 导出**：导出包含歌词信息的 MIDI 文件 +- **中文支持**：完整支持中文歌词的导入导出（UTF-8 编码） + +### 🎨 界面特性 + +- **主题切换**：支持浅色/深色主题 +- **响应式布局**：自适应窗口大小 +- **SVG 网格**：跨浏览器兼容的网格渲染 +- **状态提示**：实时显示操作状态和错误信息 + +## 🚀 快速开始 + +### 环境要求 + +- Node.js 18+ +- npm 或 yarn + +### 安装 + +```bash +# 克隆项目 +git clone +cd MIDI_Editor + +# 安装依赖 +npm install + +# 启动开发服务器 +npm run dev + +# 在局域网启动 +npm run dev -- --host 0.0.0.0 +``` + +### 构建 + +```bash +# 构建生产版本 +npm run build + +# 预览构建结果 +npm run preview +``` + +## 📖 使用指南 + +### 基本工作流 + +1. **导入 MIDI**：点击导入 MIDI 按钮选择 .mid 文件 +2. **编辑音符**：在钢琴卷帘中拖拽调整音符位置和时长 +3. **添加歌词**：在右侧列表中输入每个音符的歌词 +4. **对齐音频**（可选）：导入参考音频进行对照编辑 +5. **导出文件**：点击导出含歌词 MIDI 保存文件 + +### 快捷操作 + +| 操作 | 说明 | +|------|------| +| 双击钢琴卷帘 | 添加新音符 | +| 双击音符 | 修改歌词 | +| 拖拽音符 | 移动音符位置/音高 | +| 拖拽音符边缘 | 调整音符时长 | +| Backspace / Delete | 删除选中音符 | +| Enter | 确认数值修改 | +| Escape | 取消数值修改 | +| Ctrl(Command) + 滚轮 | 水平缩放 | +| Ctrl(Command) + Shift(Option) + 滚轮 | 垂直缩放 | + +### 播放控制 + +| 按钮 | 功能 | +|------|------| +| ⏮ | 回到开头 | +| ⏪ 2s | 后退 2 秒 | +| ▶ / ⏸ | 播放 / 暂停 | +| 2s ⏩ | 前进 2 秒 | +| ⏭ | 跳到结尾 | + +## 🛠 技术栈 + +- **前端框架**：React 19 + TypeScript +- **构建工具**：Vite 7 +- **状态管理**：Zustand +- **音频引擎**：Tone.js +- **波形显示**：WaveSurfer.js +- **MIDI 解析**：@tonejs/midi +- **样式**：CSS（自定义变量主题） + +## 📁 项目结构 + +``` +. +├── eslint.config.js +├── index.html +├── package.json +├── postcss.config.js +├── README.md +├── README_CN.md +├── tailwind.config.js +├── tsconfig.app.json +├── tsconfig.json +├── tsconfig.node.json +├── vite.config.ts +├── public/ +└── src/ + ├── App.css + ├── App.tsx + ├── constants.ts + ├── index.css + ├── main.tsx + ├── types.ts + ├── assets/ + ├── components/ + │ ├── AudioTrack.tsx + │ ├── LyricTable.tsx + │ └── PianoRoll.tsx + ├── lib/ + │ └── midi.ts + └── store/ + └── useMidiStore.ts +``` diff --git a/preprocess/tools/midi_editor/eslint.config.js b/preprocess/tools/midi_editor/eslint.config.js new file mode 100644 index 0000000..5e6b472 --- /dev/null +++ b/preprocess/tools/midi_editor/eslint.config.js @@ -0,0 +1,23 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' +import { defineConfig, globalIgnores } from 'eslint/config' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + js.configs.recommended, + tseslint.configs.recommended, + reactHooks.configs.flat.recommended, + reactRefresh.configs.vite, + ], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + }, +]) diff --git a/preprocess/tools/midi_editor/index.html b/preprocess/tools/midi_editor/index.html new file mode 100644 index 0000000..a4c2df7 --- /dev/null +++ b/preprocess/tools/midi_editor/index.html @@ -0,0 +1,13 @@ + + + + + + + midi-editor + + +
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+ "zustand": "^5.0.10" + }, + "devDependencies": { + "@eslint/js": "^9.39.1", + "@types/node": "^24.10.1", + "@types/react": "^19.2.5", + "@types/react-dom": "^19.2.3", + "@vitejs/plugin-react": "^5.1.1", + "autoprefixer": "^10.4.20", + "eslint": "^9.39.1", + "eslint-plugin-react-hooks": "^7.0.1", + "eslint-plugin-react-refresh": "^0.4.24", + "globals": "^16.5.0", + "postcss": "^8.4.47", + "tailwindcss": "^3.4.15", + "typescript": "~5.9.3", + "typescript-eslint": "^8.46.4", + "vite": "^7.2.4" + } +} diff --git a/preprocess/tools/midi_editor/postcss.config.js b/preprocess/tools/midi_editor/postcss.config.js new file mode 100644 index 0000000..2e7af2b --- /dev/null +++ b/preprocess/tools/midi_editor/postcss.config.js @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/preprocess/tools/midi_editor/public/vite.svg b/preprocess/tools/midi_editor/public/vite.svg new file mode 100644 index 0000000..e7b8dfb --- /dev/null +++ b/preprocess/tools/midi_editor/public/vite.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/preprocess/tools/midi_editor/src/App.css b/preprocess/tools/midi_editor/src/App.css new file mode 100644 index 0000000..7f5bdfa --- /dev/null +++ b/preprocess/tools/midi_editor/src/App.css @@ -0,0 +1,785 @@ +.app-shell { + padding: 24px; + color: var(--text-primary); + width: 100%; + max-width: 100%; + margin: 0; + height: 100vh; + max-height: 100vh; + display: flex; + flex-direction: column; + overflow: hidden; + box-sizing: border-box; +} + +.topbar { + display: flex; + align-items: center; + justify-content: space-between; + gap: 24px; + background: var(--panel-strong); + border: 1px solid var(--border-subtle); + border-radius: 16px; + padding: 20px 24px; + box-shadow: var(--shadow-panel); +} + +.topbar h1 { + margin: 4px 0 0 0; + font-size: 26px; + letter-spacing: -0.5px; +} + +.eyebrow { + margin: 0; + text-transform: uppercase; + font-size: 12px; + letter-spacing: 2px; + color: var(--text-muted); +} + +.muted { + margin: 6px 0 0 0; + color: var(--text-muted); +} + +.actions { + display: flex; + gap: 10px; +} + +.icon-toggle { + width: 40px; + height: 40px; + border-radius: 999px; + border: 1px solid var(--border-soft); + background: var(--button-ghost-bg); + color: var(--button-ghost-text); + display: inline-flex; + align-items: center; + justify-content: center; + font-size: 18px; + cursor: pointer; +} + +.icon-toggle:hover { + transform: translateY(-1px); +} + +.audio-bar { + margin-top: 14px; + padding: 12px 16px; + border-radius: 14px; + background: var(--panel-strong); + border: 1px solid var(--border-subtle); + display: flex; + align-items: center; + justify-content: space-between; + gap: 16px; +} + +.audio-left { + display: flex; + align-items: center; + gap: 12px; +} + +.audio-hint { + color: var(--text-muted); + font-size: 12px; +} + +.audio-right { + display: flex; + align-items: center; + gap: 20px; +} + +.volume-control { + display: flex; + align-items: center; + gap: 8px; +} + +.volume-label { + font-size: 12px; + color: var(--text-muted); + min-width: 32px; +} + +.volume-slider { + width: 80px; + height: 4px; + cursor: pointer; + accent-color: var(--accent); +} + +.volume-value { + font-size: 11px; + color: var(--text-muted); + min-width: 36px; + text-align: right; +} + +.toggle { + display: inline-flex; + align-items: center; + gap: 8px; + font-size: 13px; + color: var(--text-primary); +} + +.panel { + margin-top: 18px; + background: var(--panel); + border: 1px solid var(--border-subtle); + border-radius: 16px; + padding: 18px; + box-shadow: var(--shadow-panel); + display: flex; + flex-direction: column; + flex: 1; + min-height: 0; + overflow: hidden; +} + +.panel-split { + display: grid; + grid-template-columns: minmax(0, 1fr) 360px; + gap: 16px; + align-items: stretch; + flex: 1; + min-height: 0; + max-height: 100%; + overflow: hidden; +} + +.panel-main { + min-width: 0; + display: flex; + flex-direction: column; + min-height: 0; + max-height: 100%; + overflow: hidden; +} + +.panel-side { + display: flex; + flex-direction: column; + gap: 16px; + width: 360px; + max-width: 360px; + /* Use absolute positioning to enforce height */ + position: relative; + overflow: hidden; +} + +.controls { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(180px, 1fr)); + gap: 14px; + align-items: center; + background: var(--panel-soft); + padding: 12px 14px; + border-radius: 12px; + border: 1px solid var(--border-soft); + flex-shrink: 0; +} + +.controls label { + display: block; + font-size: 12px; + text-transform: uppercase; + letter-spacing: 1px; + color: var(--text-muted); + margin-bottom: 4px; +} + +.controls input[type='number'] { + width: 100%; + padding: 10px 12px; + border-radius: 10px; + border: 1px solid var(--border-soft); + background: var(--input-bg); + color: var(--text-primary); +} + +.timesig { + display: flex; + align-items: center; + gap: 6px; +} + +.timesig span { + font-weight: 700; + color: var(--text-muted); +} + +.transport { + display: flex; + gap: 8px; + align-items: center; +} + +.selection-controls { + display: flex; + gap: 8px; + align-items: center; + padding: 6px 0; +} + +.selection-btn { + font-size: 12px !important; + padding: 6px 10px !important; +} + +.selection-btn.active { + background: var(--accent) !important; + color: white !important; +} + +.selection-info { + font-size: 12px; + color: var(--accent); + font-weight: 500; + padding: 4px 8px; + background: rgba(var(--accent-rgb), 0.1); + border-radius: 6px; +} + +.status { + color: var(--text-muted); + font-size: 13px; +} + +.button, +.actions button, +.transport button, +.ghost, +.primary, +.soft { + cursor: pointer; + border-radius: 12px; + border: 1px solid transparent; + padding: 10px 14px; + font-weight: 600; + transition: transform 140ms ease, box-shadow 140ms ease, background 140ms ease, border 140ms ease; + color: #0f1528; +} + +.ghost { + background: var(--button-ghost-bg); + color: var(--button-ghost-text); + border-color: var(--border-soft); +} + +.primary { + background: linear-gradient(135deg, var(--accent), var(--accent-strong)); + color: var(--button-primary-text); + box-shadow: 0 8px 26px rgba(72, 228, 194, 0.2); +} + +.soft { + background: var(--button-soft-bg); + color: var(--button-soft-text); + border: 1px solid var(--border-soft); +} + +.ghost:disabled, +.primary:disabled, +.soft:disabled { + opacity: 0.6; + cursor: not-allowed; +} + +.ghost:hover, +.primary:hover, +.soft:hover { + transform: translateY(-1px); +} + +.piano-shell { + border-radius: 12px; + background: var(--panel-strong); + border: 1px solid var(--border-subtle); + overflow: hidden; + flex: 1; + min-height: 0; + max-height: 100%; + display: flex; + flex-direction: column; +} + +.ruler { + position: relative; + height: 32px; + background: var(--panel-soft); + border-bottom: 1px solid var(--border-soft); + min-width: 100%; +} + +.ruler-shell { + display: flex; +} + +.ruler-spacer { + background: var(--panel-soft); + border-bottom: 1px solid var(--border-soft); + height: 32px; +} + +.ruler-scroll { + overflow: hidden; + flex: 1; + height: 32px; + cursor: pointer; +} + +.measure-mark { + position: absolute; + top: 0; + height: 100%; + display: flex; + flex-direction: column; + align-items: flex-start; + font-size: 10px; + color: var(--text-muted); + padding-left: 4px; + border-left: 1px solid var(--border-soft); +} + +.measure-mark span { + margin-top: 2px; +} + +.ruler-playhead { + position: absolute; + top: 0; + width: 2px; + height: 100%; + background: #ff7043; + pointer-events: none; + z-index: 10; +} + +.ruler-scroll.selecting { + cursor: crosshair; +} + +.selection-range { + position: absolute; + top: 0; + height: 100%; + background: rgba(66, 165, 245, 0.35); + border-left: 2px solid #42a5f5; + border-right: 2px solid #42a5f5; + pointer-events: none; + z-index: 5; +} + +.grid-selection-range { + position: absolute; + top: 0; + background: rgba(66, 165, 245, 0.15); + border-left: 2px dashed #42a5f5; + border-right: 2px dashed #42a5f5; + pointer-events: none; + z-index: 1; +} + +.roll-body { + display: flex; + flex: 1; + min-height: 0; + overflow: hidden; +} + +.pitch-rail { + background: var(--panel-strong); + border-right: 1px solid var(--border-subtle); + color: var(--text-primary); + font-size: 12px; + text-align: right; + overflow: hidden; + flex-shrink: 0; + height: 100%; +} + +.pitch-cell { + border-bottom: 1px solid var(--border-soft); + display: flex; + align-items: center; + justify-content: flex-end; + padding: 0 4px; + font-variant-numeric: tabular-nums; + box-sizing: border-box; +} + +.pitch-white { + background: rgba(255, 255, 255, 0.06); + color: var(--text-primary); +} + +.pitch-black { + background: rgba(0, 0, 0, 0.35); + color: rgba(233, 238, 247, 0.9); +} + +.pitch-c { + background: rgba(100, 150, 255, 0.15); + font-weight: 600; +} + +.pitch-label { + font-size: 10px; +} + +.roll-grid { + position: relative; + overflow: auto; + flex: 1; + min-height: 0; + background-color: var(--grid-bg); +} + +.grid-content { + background-color: var(--grid-bg); +} + +.grid-svg { + shape-rendering: crispEdges; +} + +.grid-overlay { + position: relative; +} + +.note-chip { + position: absolute; + background: linear-gradient(135deg, var(--accent), var(--accent-strong)); + border-radius: 6px; + border: 1px solid rgba(255, 255, 255, 0.16); + box-shadow: 0 10px 22px rgba(0, 0, 0, 0.25); + display: flex; + align-items: center; + justify-content: center; + color: var(--note-text); + font-weight: 700; + user-select: none; + box-sizing: border-box; +} + +.note-active { + outline: 2px solid #ff7043; + z-index: 2; +} + +.note-overlap { + background: linear-gradient(135deg, #ef5350 0%, #ff7043 100%) !important; + animation: pulse-overlap 1s ease-in-out infinite; +} + +/* Selected overlapping note - more visible outline */ +.note-overlap.note-active { + outline: 3px solid #1e40af; + outline-offset: 1px; + box-shadow: 0 0 12px rgba(30, 64, 175, 0.8); + animation: none; +} + +@keyframes pulse-overlap { + 0%, 100% { opacity: 1; } + 50% { opacity: 0.7; } +} + +.playhead { + position: absolute; + top: 0; + width: 2px; + background: #ff7043; + box-shadow: 0 0 12px rgba(255, 112, 67, 0.6); + pointer-events: none; + z-index: 20; +} + +.pitch-rail-inner { + will-change: transform; +} + +.note-label { + width: 100%; + text-align: center; + font-size: 12px; + padding: 0 12px; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; +} + +.note-handle { + position: absolute; + top: 0; + width: 8px; + height: 100%; + background: rgba(255, 255, 255, 0.25); + cursor: ew-resize; +} + +.note-handle.start { + left: 0; + border-radius: 6px 0 0 6px; +} + +.note-handle.end { + right: 0; + border-radius: 0 6px 6px 0; +} + +.lyric-container { + flex: 1; + min-height: 0; + position: relative; +} + +.lyric-card { + border: 1px solid rgba(255, 255, 255, 0.06); + border-radius: 12px; + background: var(--panel-soft); + overflow: hidden; + display: flex; + flex-direction: column; + /* Force fixed height with absolute positioning */ + position: absolute; + top: 0; + left: 0; + right: 0; + bottom: 0; +} + +.lyric-bulk { + display: flex; + gap: 8px; + padding: 10px 12px; + border-bottom: 1px solid rgba(255, 255, 255, 0.06); + align-items: center; +} + +.lyric-bulk-input { + flex: 1; + padding: 8px 10px; + border-radius: 10px; + border: 1px solid var(--border-soft); + background: var(--input-bg); + color: var(--text-primary); + resize: vertical; +} + +.lyric-header, +.lyric-row { + display: grid; + grid-template-columns: 1.4fr 0.5fr 0.5fr 0.5fr; + gap: 8px; + padding: 10px 12px; + align-items: center; +} + +.lyric-header { + font-size: 12px; + text-transform: uppercase; + letter-spacing: 1px; + color: var(--text-muted); + border-bottom: 1px solid rgba(255, 255, 255, 0.06); +} + +.lyric-list { + overflow-y: auto; + overflow-x: hidden; + flex: 1; + min-height: 0; +} + +.lyric-row { + border-bottom: 1px solid rgba(255, 255, 255, 0.04); +} + +.lyric-row:hover { + background: rgba(255, 255, 255, 0.03); +} + +.lyric-row-active { + background: rgba(72, 228, 194, 0.08); + border-left: 3px solid #48e4c2; +} + +.lyric-input { + width: 100%; + padding: 8px 10px; + border-radius: 10px; + border: 1px solid var(--border-soft); + background: var(--input-bg); + color: var(--text-primary); +} + +.lyric-meta { + color: var(--text-muted); + font-variant-numeric: tabular-nums; +} + +.editable-cell { + position: relative; + display: flex; + align-items: center; + gap: 2px; +} + +.lyric-meta-input { + width: 100%; + padding: 2px 4px; + border: 1px solid transparent; + border-radius: 4px; + background: transparent; + color: var(--text-muted); + font-size: 12px; + font-variant-numeric: tabular-nums; + text-align: center; + outline: none; + transition: border-color 0.15s, background-color 0.15s; +} + +.lyric-meta-input:hover { + background: var(--surface-elevated); +} + +.lyric-meta-input:focus { + border-color: var(--accent); + background: var(--surface-elevated); + color: var(--text-primary); +} + +.lyric-meta-dirty { + border-color: #f59e0b !important; + background: rgba(245, 158, 11, 0.1) !important; +} + +.confirm-btn { + flex-shrink: 0; + width: 18px; + height: 18px; + padding: 0; + border: none; + border-radius: 4px; + background: #22c55e; + color: white; + font-size: 12px; + font-weight: bold; + cursor: pointer; + display: flex; + align-items: center; + justify-content: center; + transition: background 0.15s; +} + +.confirm-btn:hover { + background: #16a34a; +} + +/* Hide number input spinners */ +.lyric-meta-input::-webkit-outer-spin-button, +.lyric-meta-input::-webkit-inner-spin-button { + -webkit-appearance: none; + margin: 0; +} + +.lyric-meta-input[type=number] { + -moz-appearance: textfield; +} + +.lyric-empty { + padding: 16px; + color: var(--text-muted); + text-align: center; +} + +.audio-track { + display: grid; + grid-template-columns: 80px 1fr; + gap: 12px; + align-items: center; + padding: 12px 14px; + border-radius: 12px; + border: 1px solid var(--border-soft); + background: var(--panel-soft); + margin-bottom: 12px; + flex-shrink: 0; +} + +.audio-track-label { + font-size: 12px; + text-transform: uppercase; + letter-spacing: 1px; + color: var(--text-muted); +} + +.audio-wave { + width: 100%; + height: 80px; + min-height: 80px; +} + +:root { + --text-primary: #e9eef7; + --text-muted: rgba(233, 238, 247, 0.7); + --panel: rgba(13, 16, 28, 0.8); + --panel-strong: rgba(16, 21, 35, 0.95); + --panel-soft: rgba(255, 255, 255, 0.03); + --border-subtle: rgba(255, 255, 255, 0.08); + --border-soft: rgba(255, 255, 255, 0.12); + --input-bg: rgba(255, 255, 255, 0.06); + --grid-bg: rgba(14, 18, 30, 0.9); + --grid-line-minor: rgba(233, 238, 247, 0.08); + --grid-line-major: rgba(233, 238, 247, 0.16); + --accent: #48e4c2; + --accent-strong: #4b64bc; + --note-text: #0b1122; + --button-ghost-bg: rgba(233, 238, 247, 0.18); + --button-ghost-text: #ffffff; + --button-soft-bg: rgba(255, 255, 255, 0.14); + --button-soft-text: #ffffff; + --button-primary-text: #0b1122; + --shadow-panel: 0 18px 40px rgba(0, 0, 0, 0.32); +} + +:root[data-theme='light'] { + --text-primary: #1b2238; + --text-muted: rgba(27, 34, 56, 0.7); + --panel: rgba(255, 255, 255, 0.9); + --panel-strong: rgba(250, 252, 255, 0.98); + --panel-soft: rgba(15, 23, 42, 0.04); + --border-subtle: rgba(15, 23, 42, 0.12); + --border-soft: rgba(15, 23, 42, 0.16); + --input-bg: rgba(15, 23, 42, 0.06); + --grid-bg: rgba(248, 250, 255, 0.95); + --grid-line-minor: rgba(15, 23, 42, 0.12); + --grid-line-major: rgba(15, 23, 42, 0.24); + --accent: #3f8cff; + --accent-strong: #4b64bc; + --note-text: #ffffff; + --button-ghost-bg: rgba(15, 23, 42, 0.06); + --button-ghost-text: #1b2238; + --button-soft-bg: rgba(15, 23, 42, 0.06); + --button-soft-text: #1b2238; + --button-primary-text: #0b1122; + --shadow-panel: 0 18px 40px rgba(15, 23, 42, 0.15); +} + +.sr-only { + position: absolute; + width: 1px; + height: 1px; + padding: 0; + margin: -1px; + overflow: hidden; + clip: rect(0, 0, 0, 0); + white-space: nowrap; + border: 0; +} diff --git a/preprocess/tools/midi_editor/src/App.tsx b/preprocess/tools/midi_editor/src/App.tsx new file mode 100644 index 0000000..3fb68b0 --- /dev/null +++ b/preprocess/tools/midi_editor/src/App.tsx @@ -0,0 +1,654 @@ +import { useCallback, useEffect, useMemo, useRef, useState } from 'react' +import * as Tone from 'tone' +import { PianoRoll } from './components/PianoRoll' +import { LyricTable } from './components/LyricTable' +import { AudioTrack } from './components/AudioTrack' +import { useMidiStore } from './store/useMidiStore' +import { exportMidi, importMidiFile } from './lib/midi' +import type { TimeSignature } from './types' +import { BASE_GRID_SECOND_WIDTH, BASE_ROW_HEIGHT, LOW_NOTE, HIGH_NOTE } from './constants' +import './App.css' + +type PlayEvent = { + time: number + midi: number + duration: number + velocity: number +} + +function App() { + const { + notes, + tempo, + timeSignature, + selectedId, + playhead, + ppq, + addNote, + updateNote, + removeNote, + setNotes, + setTempo, + setTimeSignature, + setPpq, + select, + setPlayhead, + } = useMidiStore() + + const [status, setStatus] = useState('准备就绪') + const [isPlaying, setIsPlaying] = useState(false) + const [theme, setTheme] = useState<'dark' | 'light'>('light') + const [audioUrl, setAudioUrl] = useState(null) + const [audioDuration, setAudioDuration] = useState(0) + const [midiVolume, setMidiVolume] = useState(80) // 0-100 + const [audioVolume, setAudioVolume] = useState(80) // 0-100 + const [horizontalZoom, setHorizontalZoom] = useState(1) + const [verticalZoom, setVerticalZoom] = useState(1) + const [focusLyricId, setFocusLyricId] = useState(null) + // Selection range for loop playback (in seconds) + const [selectionStart, setSelectionStart] = useState(null) + const [selectionEnd, setSelectionEnd] = useState(null) + const [isSelectingRange, setIsSelectingRange] = useState(false) + const fileInputRef = useRef(null) + const audioInputRef = useRef(null) + const audioRef = useRef(null) + const partRef = useRef | null>(null) + const synthRef = useRef(null) + const rafRef = useRef(null) + const audioScrollRef = useRef(null) + + useEffect(() => { + return () => { + stopPlayback() + synthRef.current?.dispose() + } + }, []) + + useEffect(() => { + document.documentElement.dataset.theme = theme + }, [theme]) + + // Sync audio volume - also trigger when audioUrl changes (new audio loaded) + useEffect(() => { + if (audioRef.current) { + audioRef.current.volume = audioVolume / 100 + } + }, [audioVolume, audioUrl]) + + // Sync MIDI synth volume + useEffect(() => { + if (synthRef.current) { + // Convert 0-100 to dB scale (-60 to 0) + const dbValue = midiVolume === 0 ? -Infinity : (midiVolume / 100) * 60 - 60 + synthRef.current.volume.value = dbValue + } + }, [midiVolume]) + + useEffect(() => { + if (!audioUrl) return + return () => { + URL.revokeObjectURL(audioUrl) + } + }, [audioUrl]) + + const ensureSynth = async () => { + await Tone.start() + if (!synthRef.current) { + synthRef.current = new Tone.PolySynth(Tone.Synth).toDestination() + // Apply current volume + const dbValue = midiVolume === 0 ? -Infinity : (midiVolume / 100) * 60 - 60 + synthRef.current.volume.value = dbValue + } + } + + const playPreviewNote = useCallback(async (midi: number) => { + await ensureSynth() + const frequency = Tone.Frequency(midi, 'midi').toFrequency() + synthRef.current?.triggerAttackRelease(frequency, '8n', Tone.now(), 0.7) + }, [midiVolume]) + + useEffect(() => { + const onKeyDown = (event: KeyboardEvent) => { + if (!selectedId) return + const target = event.target as HTMLElement | null + if (target && ['INPUT', 'TEXTAREA'].includes(target.tagName)) return + + // Delete note + if (event.key === 'Backspace' || event.key === 'Delete') { + event.preventDefault() + removeNote(selectedId) + select(null) + return + } + + // Cmd/Ctrl + Up/Down to adjust pitch + const isCmdOrCtrl = event.metaKey || event.ctrlKey + if (isCmdOrCtrl && (event.key === 'ArrowUp' || event.key === 'ArrowDown')) { + event.preventDefault() + const selectedNote = notes.find(n => n.id === selectedId) + if (!selectedNote) return + + const delta = event.key === 'ArrowUp' ? 1 : -1 + const newMidi = Math.max(LOW_NOTE, Math.min(HIGH_NOTE, selectedNote.midi + delta)) + + if (newMidi !== selectedNote.midi) { + updateNote(selectedId, { midi: newMidi }) + playPreviewNote(newMidi) + } + } + } + window.addEventListener('keydown', onKeyDown) + return () => window.removeEventListener('keydown', onKeyDown) + }, [selectedId, notes, removeNote, select, updateNote, playPreviewNote]) + + const noteEvents = useMemo( + () => + notes.map((note) => ({ + time: (60 / tempo) * note.start, + duration: (60 / tempo) * note.duration, + midi: note.midi, + velocity: note.velocity, + })), + [notes, tempo], + ) + + const beatToSeconds = (beat: number) => beat * (60 / tempo) + const secondsToBeat = (seconds: number) => seconds / (60 / tempo) + const seekBySeconds = (deltaSeconds: number) => { + const maxNoteEnd = notes.reduce((acc, n) => Math.max(acc, n.start + n.duration), 0) + const maxBeat = Math.max(secondsToBeat(audioDuration), maxNoteEnd) + const nextSeconds = Math.max(0, Math.min(beatToSeconds(maxBeat), beatToSeconds(playhead) + deltaSeconds)) + seekToBeat(secondsToBeat(nextSeconds)) + } + + const gridSecondWidth = BASE_GRID_SECOND_WIDTH * horizontalZoom + const rowHeight = BASE_ROW_HEIGHT * verticalZoom + + // Calculate MIDI content width to sync with audio track + const midiContentWidth = useMemo(() => { + const noteEndSeconds = notes.reduce((acc, n) => { + const endBeat = n.start + n.duration + return Math.max(acc, beatToSeconds(endBeat)) + }, 8) + const maxSeconds = Math.max(noteEndSeconds + 10, audioDuration + 10, 30) + return maxSeconds * gridSecondWidth + }, [notes, audioDuration, gridSecondWidth, beatToSeconds]) + + const seekToBeat = (beat: number) => { + setPlayhead(beat) + Tone.Transport.seconds = beatToSeconds(beat) + if (audioRef.current) { + audioRef.current.currentTime = beatToSeconds(beat) + } + } + + const schedulePlayback = async () => { + if (!notes.length && !audioUrl) return + await ensureSynth() + partRef.current?.dispose() + Tone.Transport.cancel() + Tone.Transport.stop() + Tone.Transport.bpm.value = tempo + + // Determine playback range + const hasSelection = selectionStart !== null && selectionEnd !== null && selectionEnd > selectionStart + const startSeconds = hasSelection ? selectionStart : beatToSeconds(playhead) + const endSeconds = hasSelection ? selectionEnd : null + + Tone.Transport.seconds = startSeconds + + // Filter notes within selection range if applicable + const filteredEvents = hasSelection + ? noteEvents.filter(e => e.time >= startSeconds && e.time < endSeconds!) + : noteEvents + + if (filteredEvents.length) { + partRef.current = new Tone.Part((time, event) => { + if (midiVolume === 0) return + const frequency = Tone.Frequency(event.midi, 'midi').toFrequency() + synthRef.current?.triggerAttackRelease(frequency, event.duration, time, event.velocity) + }, filteredEvents) + partRef.current.start(0) + } + Tone.Transport.start() + if (audioRef.current && audioUrl) { + audioRef.current.currentTime = startSeconds + if (audioVolume > 0) { + audioRef.current.play().catch(() => null) + } + } + setIsPlaying(true) + setStatus(hasSelection ? '选区回放中...' : '正在回放...') + + const tick = () => { + const seconds = + audioRef.current && audioUrl && !audioRef.current.paused + ? audioRef.current.currentTime + : Tone.Transport.seconds + + // Stop at selection end + if (endSeconds !== null && seconds >= endSeconds) { + pausePlayback() + seekToBeat(secondsToBeat(selectionStart!)) + setStatus('选区播放完毕') + return + } + + const beat = seconds / (60 / tempo) + setPlayhead(beat) + rafRef.current = requestAnimationFrame(tick) + } + rafRef.current = requestAnimationFrame(tick) + } + + const stopPlayback = () => { + Tone.Transport.stop() + Tone.Transport.cancel() + partRef.current?.dispose() + partRef.current = null + setIsPlaying(false) + setPlayhead(0) + if (audioRef.current) { + audioRef.current.pause() + audioRef.current.currentTime = 0 + } + if (rafRef.current) { + cancelAnimationFrame(rafRef.current) + rafRef.current = null + } + } + + const pausePlayback = () => { + Tone.Transport.stop() + partRef.current?.dispose() + partRef.current = null + setIsPlaying(false) + if (audioRef.current) { + audioRef.current.pause() + } + if (rafRef.current) { + cancelAnimationFrame(rafRef.current) + rafRef.current = null + } + } + + const handlePlayToggle = async () => { + if (isPlaying) { + pausePlayback() + setStatus('已暂停') + } else { + await schedulePlayback() + } + } + + const handleImportClick = () => fileInputRef.current?.click() + const handleAudioImportClick = () => audioInputRef.current?.click() + + const handleFileChange = async (event: React.ChangeEvent) => { + const file = event.target.files?.[0] + if (!file) return + + try { + const snapshot = await importMidiFile(file) + setNotes(snapshot.notes) + setTempo(snapshot.tempo) + setTimeSignature(snapshot.timeSignature as TimeSignature) + setPpq(snapshot.ppq) // Preserve original ppq for accurate export + setStatus(`已载入 ${file.name}`) + } catch (error) { + console.error(error) + setStatus('导入失败，请确认文件合法') + } finally { + event.target.value = '' + } + } + + const handleAudioChange = (event: React.ChangeEvent) => { + const file = event.target.files?.[0] + if (!file) return + + // Validate audio file type + const validAudioTypes = ['audio/mpeg', 'audio/wav', 'audio/ogg', 'audio/flac', 'audio/mp4', 'audio/aac', 'audio/x-m4a'] + const validExtensions = ['.mp3', '.wav', '.ogg', '.flac', '.m4a', '.aac'] + const fileName = file.name.toLowerCase() + const isValidType = validAudioTypes.includes(file.type) || file.type.startsWith('audio/') + const isValidExtension = validExtensions.some(ext => fileName.endsWith(ext)) + + if (!isValidType && !isValidExtension) { + setStatus(`不支持的文件格式，请选择音频文件（${validExtensions.join(', ')}）`) + event.target.value = '' + return + } + + const url = URL.createObjectURL(file) + setAudioUrl(url) + setStatus(`已载入音频 ${file.name}`) + event.target.value = '' + } + + // Check for overlapping notes (any pitch) + const getOverlappingNotes = () => { + const overlapping: string[] = [] + const sortedNotes = [...notes].sort((a, b) => a.start - b.start) + const EPSILON = 0.05 // Tolerance for floating point comparison + + for (let i = 0; i < sortedNotes.length; i++) { + for (let j = i + 1; j < sortedNotes.length; j++) { + const noteA = sortedNotes[i] + const noteB = sortedNotes[j] + const noteAEnd = noteA.start + noteA.duration + // If noteB starts at or after noteA ends (with tolerance), no overlap + if (noteB.start >= noteAEnd - EPSILON) break + // True overlap: noteB starts before noteA ends + if (!overlapping.includes(noteA.id)) overlapping.push(noteA.id) + if (!overlapping.includes(noteB.id)) overlapping.push(noteB.id) + } + } + return overlapping + } + + // Auto-fix overlapping notes by trimming the first note to end where the second begins + const handleFixOverlaps = () => { + const sortedNotes = [...notes].sort((a, b) => a.start - b.start) + let fixCount = 0 + + for (let i = 0; i < sortedNotes.length - 1; i++) { + const noteA = sortedNotes[i] + const noteB = sortedNotes[i + 1] + const noteAEnd = noteA.start + noteA.duration + + // If noteA overlaps with noteB + if (noteAEnd > noteB.start) { + // Trim noteA to end at noteB's start + const newDuration = Math.max(0.01, noteB.start - noteA.start) + updateNote(noteA.id, { duration: newDuration }) + fixCount++ + } + } + + if (fixCount > 0) { + setStatus(`已修复 ${fixCount} 个重叠音符`) + } else { + setStatus('没有检测到重叠音符') + } + } + + const handleExport = () => { + const overlapping = getOverlappingNotes() + if (overlapping.length > 0) { + const confirm = window.confirm( + `检测到 ${overlapping.length} 个音符存在时间重叠（标红色的音符），这可能导致播放异常。\n\n是否仍要导出？` + ) + if (!confirm) return + } + + const blob = exportMidi({ notes, tempo, timeSignature, ppq }) + const url = URL.createObjectURL(blob) + const anchor = document.createElement('a') + anchor.href = url + anchor.download = 'vocal-midi.mid' + anchor.click() + URL.revokeObjectURL(url) + setStatus('已导出包含歌词的 MIDI 文件') + } + + + return ( +
+
+
+

歌声 MIDI 编辑器

+

Lyric-ready Piano Roll

+

导入、拖拽、实时修改歌词并导出标准 MIDI。

+
+
+ + + + + +
+
+ +
+
+ + + 导入后显示音频波形并与 MIDI 同步走带 +
+
+
+ MIDI + setMidiVolume(Number(e.target.value))} + className="volume-slider" + /> + {midiVolume}% +
+
+ 音频 + setAudioVolume(Number(e.target.value))} + className="volume-slider" + /> + {audioVolume}% +
+
+
+ +
+
+ {audioUrl && ( + seekToBeat(secondsToBeat(seconds))} + playheadSeconds={beatToSeconds(playhead)} + gridSecondWidth={gridSecondWidth} + minContentWidth={midiContentWidth} + /> + )} + { + if (audioScrollRef.current) { + audioScrollRef.current.scrollLeft = left + } + }} + onZoom={(deltaH, deltaV) => { + if (deltaH !== 0) { + setHorizontalZoom(prev => Math.max(0.5, prev + deltaH)) + } + if (deltaV !== 0) { + setVerticalZoom(prev => Math.max(0.6, Math.min(2.5, prev + deltaV))) + } + }} + onPlayNote={playPreviewNote} + onFocusLyric={(noteId) => { + select(noteId) + setFocusLyricId(noteId) + }} + onSelectionChange={(start, end) => { + setSelectionStart(start) + setSelectionEnd(end) + }} + isSelectingRange={isSelectingRange} + audioDuration={audioDuration} + gridSecondWidth={gridSecondWidth} + rowHeight={rowHeight} + /> +
+ +
+
+ ) +} + +export default App diff --git a/preprocess/tools/midi_editor/src/components/AudioTrack.tsx b/preprocess/tools/midi_editor/src/components/AudioTrack.tsx new file mode 100644 index 0000000..a8d625f --- /dev/null +++ b/preprocess/tools/midi_editor/src/components/AudioTrack.tsx @@ -0,0 +1,182 @@ +import { useEffect, useRef, forwardRef, useState } from 'react' +import WaveSurfer from 'wavesurfer.js' +import { PITCH_WIDTH } from '../constants' + +export type AudioTrackProps = { + audioUrl: string | null + muted: boolean + onSeek: (seconds: number) => void + mediaElement?: HTMLAudioElement | null + playheadSeconds: number + gridSecondWidth: number + minContentWidth?: number // Minimum width to match MIDI editor area +} + +export const AudioTrack = forwardRef( + ({ audioUrl, muted, onSeek, playheadSeconds, gridSecondWidth, minContentWidth = 0 }, ref) => { + const containerRef = useRef(null) + const waveRef = useRef(null) + const [waveWidth, setWaveWidth] = useState(0) + + useEffect(() => { + if (!containerRef.current) return + if (!audioUrl) { + try { + waveRef.current?.destroy() + } catch { + // ignore teardown errors + } + waveRef.current = null + setWaveWidth(0) + return + } + + let cancelled = false + + // Clean up existing instance + if (waveRef.current) { + try { + waveRef.current.destroy() + } catch { + // ignore teardown errors + } + } + + waveRef.current = WaveSurfer.create({ + container: containerRef.current, + waveColor: '#4b64bc', + progressColor: '#4b64bc', + cursorColor: 'transparent', + barWidth: 2, + barGap: 2, + height: 60, + normalize: true, + minPxPerSec: gridSecondWidth, + interact: false, + hideScrollbar: true, + autoScroll: false, + }) + + waveRef.current.load(audioUrl).catch(() => null) + waveRef.current.on('error', () => null) + + waveRef.current.on('ready', () => { + if (cancelled || !waveRef.current) return + const duration = waveRef.current.getDuration() + const requiredWidth = duration * gridSecondWidth + setWaveWidth(requiredWidth) + }) + + return () => { + cancelled = true + try { + waveRef.current?.destroy() + } catch { + // ignore teardown errors + } + waveRef.current = null + } + }, [audioUrl, gridSecondWidth]) + + useEffect(() => { + if (!waveRef.current) return + waveRef.current.setOptions({ + waveColor: muted ? '#9aa6b2' : '#4b64bc', + progressColor: muted ? '#c0c9d4' : '#4b64bc', + }) + }, [muted]) + + if (!audioUrl) return null + + // Content width should be at least as wide as MIDI editor + const contentWidth = Math.max(waveWidth, minContentWidth) + + return ( +
+
+ AUDIO +
+ + {/* Scroll Mask - Controlled by parent via ref */} +
{ + const rect = e.currentTarget.getBoundingClientRect() + const scrollMask = e.currentTarget as HTMLDivElement + const x = e.clientX - rect.left + scrollMask.scrollLeft + const seconds = x / gridSecondWidth + onSeek(seconds) + }} + > + {/* Container that matches MIDI editor width */} +
0 ? contentWidth : '100%', + height: '100%', + position: 'relative' + }} + > + {/* WaveSurfer container - only as wide as audio */} +
0 ? waveWidth : '100%', + height: '100%', + position: 'absolute', + left: 0, + top: 0 + }} + /> + + {/* Custom Playhead */} +
+
+
+
+ ) + } +) diff --git a/preprocess/tools/midi_editor/src/components/LyricTable.tsx b/preprocess/tools/midi_editor/src/components/LyricTable.tsx new file mode 100644 index 0000000..0ef4600 --- /dev/null +++ b/preprocess/tools/midi_editor/src/components/LyricTable.tsx @@ -0,0 +1,288 @@ +import { useEffect, useMemo, useRef, useState } from 'react' +import type { NoteEvent } from '../types' + +export type LyricTableProps = { + notes: NoteEvent[] + selectedId: string | null + tempo: number + focusLyricId: string | null + onSelect: (id: string | null) => void + onUpdate: (id: string, patch: Partial) => void + onScrollToNote?: (noteId: string) => void + onFocusHandled?: () => void +} + +const formatSeconds = (beats: number, tempo: number) => { + const seconds = beats * (60 / tempo) + return Number.parseFloat(seconds.toFixed(2)) +} + +const secondsToBeats = (seconds: number, tempo: number) => { + return seconds * (tempo / 60) +} + +// Editable cell with confirmation +function EditableCell({ + value, + noteId, + field, + tempo, + onConfirm, + type = 'number', + min, + step +}: { + value: number + noteId: string + field: 'midi' | 'start' | 'end' + tempo: number + onConfirm: (noteId: string, field: string, value: number) => void + type?: string + min?: number + step?: number +}) { + const displayValue = field === 'midi' ? value : formatSeconds(value, tempo) + const [localValue, setLocalValue] = useState(String(displayValue)) + const [isDirty, setIsDirty] = useState(false) + const inputRef = useRef(null) + + // Sync with external value when it changes (and not dirty) + useEffect(() => { + if (!isDirty) { + setLocalValue(String(displayValue)) + } + }, [displayValue, isDirty]) + + const handleChange = (e: React.ChangeEvent) => { + setLocalValue(e.target.value) + setIsDirty(true) + } + + const handleConfirm = () => { + const parsed = parseFloat(localValue) + if (!isNaN(parsed)) { + if (field === 'midi') { + if (parsed >= 0 && parsed <= 127) { + onConfirm(noteId, field, Math.round(parsed)) + } + } else { + if (parsed >= 0) { + onConfirm(noteId, field, secondsToBeats(parsed, tempo)) + } + } + } + setIsDirty(false) + } + + const handleKeyDown = (e: React.KeyboardEvent) => { + if (e.key === 'Enter') { + e.preventDefault() + handleConfirm() + inputRef.current?.blur() + } else if (e.key === 'Escape') { + setLocalValue(String(displayValue)) + setIsDirty(false) + inputRef.current?.blur() + } + } + + const handleBlur = () => { + if (isDirty) { + // Reset to original on blur without confirm + setLocalValue(String(displayValue)) + setIsDirty(false) + } + } + + return ( +
+ e.stopPropagation()} + /> + {isDirty && ( + + )} +
+ ) +} + +export function LyricTable({ notes, selectedId, tempo, focusLyricId, onSelect, onUpdate, onScrollToNote, onFocusHandled }: LyricTableProps) { + const listRef = useRef(null) + const inputRefs = useRef>(new Map()) + const sorted = useMemo(() => [...notes].sort((a, b) => a.start - b.start), [notes]) + + // Scroll to selected note (no auto-focus on single click) + useEffect(() => { + if (!selectedId || !listRef.current) return + + const target = listRef.current.querySelector(`[data-note-id="${selectedId}"]`) + if (target) { + target.scrollIntoView({ block: 'nearest', behavior: 'smooth' }) + } + }, [selectedId]) + + // Focus lyric input when requested (double-click on note or click on list row) + useEffect(() => { + if (!focusLyricId) return + + const input = inputRefs.current.get(focusLyricId) + if (input) { + setTimeout(() => { + input.focus() + input.select() + }, 50) + } + onFocusHandled?.() + }, [focusLyricId, onFocusHandled]) + + // Fill lyrics from selected note onwards + const handleBulkFill = (bulkText: string) => { + if (!sorted.length) return + const chars = Array.from(bulkText.replace(/\s+/g, '')) + + let startIndex = 0 + if (selectedId) { + const selectedIndex = sorted.findIndex(n => n.id === selectedId) + if (selectedIndex >= 0) { + startIndex = selectedIndex + } + } + + let charIndex = 0 + for (let i = startIndex; i < sorted.length && charIndex < chars.length; i++) { + onUpdate(sorted[i].id, { lyric: chars[charIndex] }) + charIndex++ + } + } + + const handleRowClick = (noteId: string) => { + onSelect(noteId) + onScrollToNote?.(noteId) + } + + const handleFieldConfirm = (noteId: string, field: string, value: number) => { + const note = notes.find(n => n.id === noteId) + if (!note) return + + if (field === 'midi') { + onUpdate(noteId, { midi: value }) + } else if (field === 'start') { + // Keep END the same, adjust duration accordingly + const currentEnd = note.start + note.duration + const newDuration = Math.max(0.01, currentEnd - value) + onUpdate(noteId, { start: value, duration: newDuration }) + } else if (field === 'end') { + // End changed, update duration + const newDuration = Math.max(0.01, value - note.start) + onUpdate(noteId, { duration: newDuration }) + } + } + + return ( +
+
+