mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-04-05 19:41:56 +08:00
增加了自动填充路径的功能，增加了根据显存自动选择ASR精度的功能,也可手动控制
增加了自动填充路径的功能 增加了根据显存自动选择ASR精度的功能,也可手动控制
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@ -106,7 +106,7 @@ conda install -c conda-forge 'ffmpeg<7'
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Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root.
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##### Mac Users
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##### MacOS Users
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```bash
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brew install ffmpeg
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```
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@ -156,7 +156,7 @@ For English or Japanese ASR (additionally), download models from [Faster Whisper
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Users in the China region can download this model by entering the links below
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- [Faster Whisper Large V3](https://www.icloud.com/iclouddrive/0c4pQxFs7oWyVU1iMTq2DbmLA#faster-whisper-large-v3) (Click "Download a copy", log out if you encounter errors while downloading.)
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- [Faster Whisper Large V3](https://www.icloud.com/iclouddrive/00bUEp9_mcjMq_dhHu_vrAFDQ#faster-whisper-large-v3) (Click "Download a copy", log out if you encounter errors while downloading.)
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- [Faster Whisper Large V3](https://hf-mirror.com/Systran/faster-whisper-large-v3) (HuggingFace mirror site)
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@ -227,7 +227,7 @@ ASR processing is performed through Faster_Whisper(ASR marking except Chinese)
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(No progress bars, GPU performance may cause time delays)
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```
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language>
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language> -p <precision>
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```
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A custom list save path is enabled
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@ -106,7 +106,7 @@ conda install -c conda-forge 'ffmpeg<7'
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下载并将 [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) 和 [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) 放置在 GPT-SoVITS 根目录下。
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##### Mac 用户
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##### MacOS 用户
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```bash
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brew install ffmpeg
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```
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@ -155,7 +155,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
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对于英语与日语自动语音识别（附加）,从 [Faster Whisper Large V3](https://huggingface.co/Systran/faster-whisper-large-v3) 下载模型，并将它们放置在 `tools/asr/models` 中。 此外，[其他模型](https://huggingface.co/Systran)可能具有类似效果，但占用更小的磁盘空间。
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中国地区用户可以通过以下链接下载：
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- [Faster Whisper Large V3](https://www.icloud.com/iclouddrive/0c4pQxFs7oWyVU1iMTq2DbmLA#faster-whisper-large-v3)（点击“下载副本”，如果下载时遇到错误，请退出登录）
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- [Faster Whisper Large V3](https://www.icloud.com/iclouddrive/00bUEp9_mcjMq_dhHu_vrAFDQ#faster-whisper-large-v3)(点击“下载副本”，如果下载时遇到错误，请退出登录）
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- [Faster Whisper Large V3](https://hf-mirror.com/Systran/faster-whisper-large-v3)(Hugging Face镜像站)
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@ -185,7 +185,7 @@ D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin.
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- [ ] **高优先级：**
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- [x] 日语和英语的本地化。
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- [ ] 用户指南。
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- [x] 用户指南。
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- [x] 日语和英语数据集微调训练。
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- [ ] **功能:**
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@ -226,9 +226,9 @@ python tools/asr/funasr_asr.py -i <input> -o <output>
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通过Faster_Whisper进行ASR处理（除中文之外的ASR标记）
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（没有进度条，GPU性能可能会导致时间延迟）
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````
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language>
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````
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```
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language> -p <precision>
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```
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启用自定义列表保存路径
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## 致谢
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@ -102,7 +102,7 @@ conda install -c conda-forge 'ffmpeg<7'
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[ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) と [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) をダウンロードし、GPT-SoVITS のルートディレクトリに置きます。
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##### Mac ユーザー
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##### MacOS ユーザー
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```bash
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brew install ffmpeg
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```
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@ -209,7 +209,7 @@ ASR処理はFaster_Whisperを通じて実行されます(中国語を除くASR
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(進行状況バーは表示されません。GPU のパフォーマンスにより時間遅延が発生する可能性があります)
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```
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language>
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language> -p <precision>
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```
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カスタムリストの保存パスが有効になっています
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@ -102,7 +102,7 @@ conda install -c conda-forge 'ffmpeg<7'
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[ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe)와 [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe)를 GPT-SoVITS root 디렉토리에 넣습니다.
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##### Mac 사용자
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##### MacOS 사용자
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```bash
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brew install ffmpeg
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```
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@ -213,7 +213,7 @@ ASR 처리는 Faster_Whisper(중국어를 제외한 ASR 마킹)를 통해 수행
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(진행률 표시줄 없음, GPU 성능으로 인해 시간 지연이 발생할 수 있음)
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```
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language>
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python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language> -p <precision>
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```
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사용자 정의 목록 저장 경로가 활성화되었습니다.
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@ -102,7 +102,7 @@ conda install -c conda-forge 'ffmpeg<7'
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[ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) ve [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) dosyalarını indirin ve GPT-SoVITS kök dizinine yerleştirin.
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##### Mac Kullanıcıları
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##### MacOS Kullanıcıları
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```bash
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brew install ffmpeg
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```
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@ -21,11 +21,13 @@ asr_dict = {
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'lang': ['zh'],
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'size': ['large'],
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'path': 'funasr_asr.py',
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'precision': ['float32']
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},
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"Faster Whisper (多语种)": {
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'lang': ['auto', 'zh', 'en', 'ja'],
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'size': check_fw_local_models(),
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'path': 'fasterwhisper_asr.py'
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}
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'path': 'fasterwhisper_asr.py',
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'precision': ['float32', 'float16', 'int8']
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},
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}
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@ -101,8 +101,8 @@ if __name__ == '__main__':
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parser.add_argument("-l", "--language", type=str, default='ja',
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choices=language_code_list,
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help="Language of the audio files.")
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parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16','float32'],
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help="fp16 or fp32")
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parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16','float32','int8'],
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help="fp16, int8 or fp32")
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cmd = parser.parse_args()
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output_file_path = execute_asr(
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@ -4,7 +4,8 @@ import argparse
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import os
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import traceback
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from tqdm import tqdm
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# from funasr.utils import version_checker
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# version_checker.check_for_update = lambda: None
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from funasr import AutoModel
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path_asr = 'tools/asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'
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@ -14,6 +15,7 @@ path_asr = path_asr if os.path.exists(path_asr) else "iic/speech_paraformer-l
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path_vad = path_vad if os.path.exists(path_vad) else "iic/speech_fsmn_vad_zh-cn-16k-common-pytorch"
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path_punc = path_punc if os.path.exists(path_punc) else "iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
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model = AutoModel(
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model = path_asr,
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model_revision = "v2.0.4",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Reverberation and delay removal model(by FoxJoy):",
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"ASR 模型": "ASR model",
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"ASR 模型尺寸": "ASR model size",
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"数据类型精度": "Computing precision",
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"ASR 语言设置": "ASR language",
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"ASR进程输出信息": "ASR output log",
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"GPT模型列表": "GPT weight list",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Modelos de eliminación de reverberación y retardo (por FoxJoy)",
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"ASR 模型": "Modelo ASR",
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"ASR 模型尺寸": "Tamaño del modelo ASR",
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"数据类型精度": "precisión del tipo de datos",
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"ASR 语言设置": "Configuración del idioma ASR",
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"ASR进程输出信息": "Información de salida del proceso ASR",
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"GPT模型列表": "Lista de modelos GPT",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Modèle de suppression de réverbération et de retard (par FoxJoy) :",
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"ASR 模型": "Modèle ASR",
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"ASR 模型尺寸": "Taille du modèle ASR",
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"数据类型精度": "précision du type de données",
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"ASR 语言设置": "Paramètres de langue ASR",
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"ASR进程输出信息": "Informations de processus ASR",
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"GPT模型列表": "Liste des modèles GPT",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Modello per rimuovere la riverberazione e il ritardo (by FoxJoy):",
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"ASR 模型": "Modello ASR",
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"ASR 模型尺寸": "Dimensioni del modello ASR",
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"数据类型精度": "precisione del tipo di dati",
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"ASR 语言设置": "Impostazioni linguistiche ASR",
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"ASR进程输出信息": "Informazioni sull'output del processo ASR",
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"GPT模型列表": "Elenco dei modelli GPT",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3、リバーブ除去と遅延除去モデル（by FoxJoy）：",
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"ASR 模型": "ASR モデル",
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"ASR 模型尺寸": "ASRモデルサイズ",
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"数据类型精度": "データ型の精度",
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"ASR 语言设置": "ASR 言語設定",
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"ASR进程输出信息": "ASRプロセスの出力情報",
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"GPT模型列表": "GPTモデルリスト",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. 잔향 제거 및 지연 제거 모델 (by FoxJoy):",
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"ASR 模型": "ASR 모델",
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"ASR 模型尺寸": "ASR 모델 크기",
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"数据类型精度": "데이터 유형 정밀도",
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"ASR 语言设置": "ASR 언어 설정",
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"ASR进程输出信息": "ASR 프로세스 출력 정보",
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"GPT模型列表": "GPT 모델 목록",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Modelo de remoção de reverberação e atraso (por FoxJoy):",
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"ASR 模型": "Modelo ASR",
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"ASR 模型尺寸": "Tamanho do modelo ASR",
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"数据类型精度": "precisão do tipo de dado",
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"ASR 语言设置": "Configurações de idioma do ASR",
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"ASR进程输出信息": "Informações de saída do processo ASR",
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"GPT模型列表": "Lista de modelos GPT",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Модель удаления реверберации и задержек (от FoxJoy):",
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"ASR 模型": "Модель ASR",
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"ASR 模型尺寸": "Размер модели ASR",
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"数据类型精度": "точность типа данных",
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"ASR 语言设置": "Настройки языка ASR",
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"ASR进程输出信息": "Информация о процессе ASR",
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"GPT模型列表": "Список моделей GPT",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3. Yankı ve gecikme giderme modeli (FoxJoy tarafından):",
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"ASR 模型": "ASR modeli",
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"ASR 模型尺寸": "ASR model boyutu",
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"数据类型精度": "veri türü doğruluğu",
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"ASR 语言设置": "ASR dil ayarları",
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"ASR进程输出信息": "ASR işlemi çıktı bilgisi",
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"GPT模型列表": "GPT model listesi",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3、去混响、去延迟模型（by FoxJoy）：",
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"ASR 模型": "ASR 模型",
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"ASR 模型尺寸": "ASR 模型尺寸",
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"数据类型精度": "数据类型精度",
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"ASR 语言设置": "ASR 语言设置",
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"ASR进程输出信息": "ASR进程输出信息",
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"GPT模型列表": "GPT模型列表",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3、去混響、去延遲模型（by FoxJoy）：",
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"ASR 模型": "ASR 模型",
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"ASR 模型尺寸": "ASR 模型尺寸",
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"数据类型精度": "數據類型精度",
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"ASR 语言设置": "ASR 語言設置",
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"ASR进程输出信息": "ASR進程輸出信息",
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"GPT模型列表": "GPT模型列表",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3、去混響、去延遲模型（by FoxJoy）：",
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"ASR 模型": "ASR 模型",
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"ASR 模型尺寸": "ASR 模型尺寸",
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"数据类型精度": "數據類型精度",
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"ASR 语言设置": "ASR 語言設定",
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"ASR进程输出信息": "ASR進程輸出資訊",
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"GPT模型列表": "GPT模型列表",
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@ -34,6 +34,7 @@
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"3、去混响、去延迟模型（by FoxJoy）：": "3、去混響、去延遲模型（by FoxJoy）：",
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"ASR 模型": "ASR 模型",
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"ASR 模型尺寸": "ASR 模型尺寸",
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"数据类型精度": "數據類型精度",
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"ASR 语言设置": "ASR 語言設置",
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"ASR进程输出信息": "ASR進程輸出資訊",
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"GPT模型列表": "GPT模型列表",
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134
webui.py
134
webui.py
@ -195,7 +195,7 @@ def change_tts_inference(if_tts,bert_path,cnhubert_base_path,gpu_number,gpt_path
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yield i18n("TTS推理进程已关闭")
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from tools.asr.config import asr_dict
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def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
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def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, asr_precision):
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global p_asr
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if(p_asr==None):
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asr_inp_dir=my_utils.clean_path(asr_inp_dir)
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@ -205,16 +205,18 @@ def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
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cmd += f' -o "{asr_opt_dir}"'
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cmd += f' -s {asr_model_size}'
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cmd += f' -l {asr_lang}'
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cmd += " -p %s"%("float16"if is_half==True else "float32")
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yield "ASR任务开启：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True}
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cmd += f" -p {asr_precision}"
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output_file_name = os.path.basename(asr_inp_dir)
|
||||
output_folder = asr_opt_dir or "output/asr_opt"
|
||||
output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')
|
||||
yield "ASR任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}
|
||||
print(cmd)
|
||||
p_asr = Popen(cmd, shell=True)
|
||||
p_asr.wait()
|
||||
p_asr=None
|
||||
yield f"ASR任务完成, 查看终端进行下一步",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield f"ASR任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":output_file_path}
|
||||
else:
|
||||
yield "已有正在进行的ASR任务，需先终止才能开启下一次任务",{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "已有正在进行的ASR任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}
|
||||
# return None
|
||||
|
||||
def close_asr():
|
||||
@ -222,7 +224,7 @@ def close_asr():
|
||||
if(p_asr!=None):
|
||||
kill_process(p_asr.pid)
|
||||
p_asr=None
|
||||
return "已终止ASR进程",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
return "已终止ASR进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
def open_denoise(denoise_inp_dir, denoise_opt_dir):
|
||||
global p_denoise
|
||||
if(p_denoise==None):
|
||||
@ -230,14 +232,14 @@ def open_denoise(denoise_inp_dir, denoise_opt_dir):
|
||||
denoise_opt_dir=my_utils.clean_path(denoise_opt_dir)
|
||||
cmd = '"%s" tools/cmd-denoise.py -i "%s" -o "%s" -p %s'%(python_exec,denoise_inp_dir,denoise_opt_dir,"float16"if is_half==True else "float32")
|
||||
|
||||
yield "语音降噪任务开启：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "语音降噪任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}
|
||||
print(cmd)
|
||||
p_denoise = Popen(cmd, shell=True)
|
||||
p_denoise.wait()
|
||||
p_denoise=None
|
||||
yield f"语音降噪任务完成, 查看终端进行下一步",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield f"语音降噪任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":denoise_opt_dir}
|
||||
else:
|
||||
yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务",{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}
|
||||
# return None
|
||||
|
||||
def close_denoise():
|
||||
@ -245,7 +247,7 @@ def close_denoise():
|
||||
if(p_denoise!=None):
|
||||
kill_process(p_denoise.pid)
|
||||
p_denoise=None
|
||||
return "已终止语音降噪进程",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
return "已终止语音降噪进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
|
||||
p_train_SoVITS=None
|
||||
def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D):
|
||||
@ -275,21 +277,21 @@ def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_s
|
||||
with open(tmp_config_path,"w")as f:f.write(json.dumps(data))
|
||||
|
||||
cmd = '"%s" GPT_SoVITS/s2_train.py --config "%s"'%(python_exec,tmp_config_path)
|
||||
yield "SoVITS训练开始：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "SoVITS训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
|
||||
print(cmd)
|
||||
p_train_SoVITS = Popen(cmd, shell=True)
|
||||
p_train_SoVITS.wait()
|
||||
p_train_SoVITS=None
|
||||
yield "SoVITS训练完成",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "SoVITS训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
else:
|
||||
yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务",{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
|
||||
|
||||
def close1Ba():
|
||||
global p_train_SoVITS
|
||||
if(p_train_SoVITS!=None):
|
||||
kill_process(p_train_SoVITS.pid)
|
||||
p_train_SoVITS=None
|
||||
return "已终止SoVITS训练",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
return "已终止SoVITS训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
|
||||
p_train_GPT=None
|
||||
def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers,pretrained_s1):
|
||||
@ -322,21 +324,21 @@ def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_
|
||||
with open(tmp_config_path, "w") as f:f.write(yaml.dump(data, default_flow_style=False))
|
||||
# cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" --train_semantic_path "%s/6-name2semantic.tsv" --train_phoneme_path "%s/2-name2text.txt" --output_dir "%s/logs_s1"'%(python_exec,tmp_config_path,s1_dir,s1_dir,s1_dir)
|
||||
cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" '%(python_exec,tmp_config_path)
|
||||
yield "GPT训练开始：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "GPT训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
|
||||
print(cmd)
|
||||
p_train_GPT = Popen(cmd, shell=True)
|
||||
p_train_GPT.wait()
|
||||
p_train_GPT=None
|
||||
yield "GPT训练完成",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "GPT训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
else:
|
||||
yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务",{"__type__":"update","visible":False},{"__type__":"update","visible":True}
|
||||
yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
|
||||
|
||||
def close1Bb():
|
||||
global p_train_GPT
|
||||
if(p_train_GPT!=None):
|
||||
kill_process(p_train_GPT.pid)
|
||||
p_train_GPT=None
|
||||
return "已终止GPT训练",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
return "已终止GPT训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
|
||||
ps_slice=[]
|
||||
def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_parts):
|
||||
@ -344,12 +346,12 @@ def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_k
|
||||
inp = my_utils.clean_path(inp)
|
||||
opt_root = my_utils.clean_path(opt_root)
|
||||
if(os.path.exists(inp)==False):
|
||||
yield "输入路径不存在",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "输入路径不存在", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}
|
||||
return
|
||||
if os.path.isfile(inp):n_parts=1
|
||||
elif os.path.isdir(inp):pass
|
||||
else:
|
||||
yield "输入路径存在但既不是文件也不是文件夹",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "输入路径存在但既不是文件也不是文件夹", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}
|
||||
return
|
||||
if (ps_slice == []):
|
||||
for i_part in range(n_parts):
|
||||
@ -357,13 +359,13 @@ def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_k
|
||||
print(cmd)
|
||||
p = Popen(cmd, shell=True)
|
||||
ps_slice.append(p)
|
||||
yield "切割执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
|
||||
yield "切割执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}
|
||||
for p in ps_slice:
|
||||
p.wait()
|
||||
ps_slice=[]
|
||||
yield "切割结束",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "切割结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}
|
||||
else:
|
||||
yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
|
||||
yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}
|
||||
|
||||
def close_slice():
|
||||
global ps_slice
|
||||
@ -470,7 +472,7 @@ def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir):
|
||||
for p in ps1b:
|
||||
p.wait()
|
||||
ps1b=[]
|
||||
yield "SSL提取进程结束",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "SSL提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
else:
|
||||
yield "已有正在进行的SSL提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
|
||||
|
||||
@ -527,7 +529,7 @@ def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path):
|
||||
with open(path_semantic, "w", encoding="utf8") as f:
|
||||
f.write("\n".join(opt) + "\n")
|
||||
ps1c=[]
|
||||
yield "语义token提取进程结束",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
|
||||
yield "语义token提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
|
||||
else:
|
||||
yield "已有正在进行的语义token提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
|
||||
|
||||
@ -692,33 +694,37 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
|
||||
uvr5_info = gr.Textbox(label=i18n("UVR5进程输出信息"))
|
||||
gr.Markdown(value=i18n("0b-语音切分工具"))
|
||||
with gr.Row():
|
||||
with gr.Row():
|
||||
slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="")
|
||||
slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt")
|
||||
threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34")
|
||||
min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000")
|
||||
min_interval=gr.Textbox(label=i18n("min_interval:最短切割间隔"),value="300")
|
||||
hop_size=gr.Textbox(label=i18n("hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）"),value="10")
|
||||
max_sil_kept=gr.Textbox(label=i18n("max_sil_kept:切完后静音最多留多长"),value="500")
|
||||
with gr.Row():
|
||||
open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True)
|
||||
close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False)
|
||||
_max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("max:归一化后最大值多少"),value=0.9,interactive=True)
|
||||
alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True)
|
||||
n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True)
|
||||
slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息"))
|
||||
with gr.Column(scale=3):
|
||||
with gr.Row():
|
||||
slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="")
|
||||
slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt")
|
||||
with gr.Row():
|
||||
threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34")
|
||||
min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000")
|
||||
min_interval=gr.Textbox(label=i18n("min_interval:最短切割间隔"),value="300")
|
||||
hop_size=gr.Textbox(label=i18n("hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）"),value="10")
|
||||
max_sil_kept=gr.Textbox(label=i18n("max_sil_kept:切完后静音最多留多长"),value="500")
|
||||
with gr.Row():
|
||||
_max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("max:归一化后最大值多少"),value=0.9,interactive=True)
|
||||
alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True)
|
||||
n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True)
|
||||
with gr.Row():
|
||||
slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息"))
|
||||
open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True)
|
||||
close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False)
|
||||
gr.Markdown(value=i18n("0bb-语音降噪工具"))
|
||||
with gr.Row():
|
||||
with gr.Column(scale=3):
|
||||
with gr.Row():
|
||||
denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="")
|
||||
denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt")
|
||||
with gr.Row():
|
||||
denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息"))
|
||||
open_denoise_button = gr.Button(i18n("开启语音降噪"), variant="primary",visible=True)
|
||||
close_denoise_button = gr.Button(i18n("终止语音降噪进程"), variant="primary",visible=False)
|
||||
denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="")
|
||||
denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt")
|
||||
denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息"))
|
||||
gr.Markdown(value=i18n("0c-中文批量离线ASR工具"))
|
||||
with gr.Row():
|
||||
open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True)
|
||||
close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False)
|
||||
with gr.Column():
|
||||
with gr.Column(scale=3):
|
||||
with gr.Row():
|
||||
asr_inp_dir = gr.Textbox(
|
||||
label=i18n("输入文件夹路径"),
|
||||
@ -749,17 +755,39 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
|
||||
interactive = True,
|
||||
value="zh"
|
||||
)
|
||||
asr_precision = gr.Dropdown(
|
||||
label = i18n("数据类型精度"),
|
||||
choices = ["float32"],
|
||||
interactive = True,
|
||||
value="float32"
|
||||
)
|
||||
with gr.Row():
|
||||
asr_info = gr.Textbox(label=i18n("ASR进程输出信息"))
|
||||
asr_info = gr.Textbox(label=i18n("ASR进程输出信息"))
|
||||
open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True)
|
||||
close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False)
|
||||
|
||||
def change_lang_choices(key): #根据选择的模型修改可选的语言
|
||||
# return gr.Dropdown(choices=asr_dict[key]['lang'])
|
||||
return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]}
|
||||
def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸
|
||||
# return gr.Dropdown(choices=asr_dict[key]['size'])
|
||||
return {"__type__": "update", "choices": asr_dict[key]['size']}
|
||||
return {"__type__": "update", "choices": asr_dict[key]['size'],"value":asr_dict[key]['size'][-1]}
|
||||
def change_precision_choices(key): #根据选择的模型修改可选的语言
|
||||
if key =="Faster Whisper (多语种)":
|
||||
if default_batch_size <= 4:
|
||||
precision = 'int8'
|
||||
elif is_half:
|
||||
precision = 'float16'
|
||||
else:
|
||||
precision = 'float32'
|
||||
else:
|
||||
precision = 'float32'
|
||||
# return gr.Dropdown(choices=asr_dict[key]['precision'])
|
||||
return {"__type__": "update", "choices": asr_dict[key]['precision'],"value":precision}
|
||||
asr_model.change(change_lang_choices, [asr_model], [asr_lang])
|
||||
asr_model.change(change_size_choices, [asr_model], [asr_size])
|
||||
asr_model.change(change_precision_choices, [asr_model], [asr_precision])
|
||||
|
||||
|
||||
gr.Markdown(value=i18n("0d-语音文本校对标注工具"))
|
||||
with gr.Row():
|
||||
@ -772,11 +800,11 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
|
||||
label_info = gr.Textbox(label=i18n("打标工具进程输出信息"))
|
||||
if_label.change(change_label, [if_label,path_list], [label_info])
|
||||
if_uvr5.change(change_uvr5, [if_uvr5], [uvr5_info])
|
||||
open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang], [asr_info,open_asr_button,close_asr_button])
|
||||
open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang, asr_precision], [asr_info,open_asr_button,close_asr_button,path_list])
|
||||
close_asr_button.click(close_asr, [], [asr_info,open_asr_button,close_asr_button])
|
||||
open_slicer_button.click(open_slice, [slice_inp_path,slice_opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_process], [slicer_info,open_slicer_button,close_slicer_button])
|
||||
open_slicer_button.click(open_slice, [slice_inp_path,slice_opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_process], [slicer_info,open_slicer_button,close_slicer_button,asr_inp_dir,denoise_input_dir])
|
||||
close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button])
|
||||
open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button])
|
||||
open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button,asr_inp_dir])
|
||||
close_denoise_button.click(close_denoise, [], [denoise_info,open_denoise_button,close_denoise_button])
|
||||
|
||||
with gr.TabItem(i18n("1-GPT-SoVITS-TTS")):
|
||||
@ -879,4 +907,4 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
|
||||
share=is_share,
|
||||
server_port=webui_port_main,
|
||||
quiet=True,
|
||||
)
|
||||
)
|
||||
Loading…
x
Reference in New Issue
Block a user