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README.md
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README.md
@ -147,15 +147,7 @@ Users in China region can download these two models by entering the links below
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- [UVR5 Weights](https://www.icloud.com.cn/iclouddrive/0bekRKDiJXboFhbfm3lM2fVbA#UVR5_Weights)
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For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/asr/models`.
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For English or Japanese ASR (additionally), download models from [Faster Whisper Large V3](https://huggingface.co/Systran/faster-whisper-large-v3) and place them in `tools/asr/models`. Also, [other models](https://huggingface.co/Systran) may have the similar effect with smaller disk footprint.
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Users in 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) (clicking "Download a copy")
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- [Faster Whisper Large V3](https://hf-mirror.com/Systran/faster-whisper-large-v3) (HuggingFace mirror site)
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For Multilingual ASR, download models from [FunAudioLLM/SenseVoiceSmall](https://huggingface.co/FunAudioLLM/SenseVoiceSmall/tree/main) or [iic/SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/files) and place them in `tools/asr/models`.
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## Dataset Format
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@ -216,16 +208,11 @@ python audio_slicer.py \
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--min_interval <shortest_time_gap_between_adjacent_subclips>
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--hop_size <step_size_for_computing_volume_curve>
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```
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This is how dataset ASR processing is done using the command line(Only Chinese)
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This is how dataset ASR processing is done using the command line
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```
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python tools/asr/funasr_asr.py -i <input> -o <output>
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python tools/asr/sensevoice.py -i <input> -o <output> -l <language> -d <device>
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```
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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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```
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A custom list save path is enabled
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## Credits
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@ -252,8 +239,7 @@ Special thanks to the following projects and contributors:
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- [SubFix](https://github.com/cronrpc/SubFix)
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- [FFmpeg](https://github.com/FFmpeg/FFmpeg)
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- [gradio](https://github.com/gradio-app/gradio)
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- [faster-whisper](https://github.com/SYSTRAN/faster-whisper)
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- [FunASR](https://github.com/alibaba-damo-academy/FunASR)
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- [SenseVoice](https://github.com/FunAudioLLM/SenseVoice)
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## Thanks to all contributors for their efforts
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@ -147,14 +147,8 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
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- [UVR5 Weights](https://www.icloud.com.cn/iclouddrive/0bekRKDiJXboFhbfm3lM2fVbA#UVR5_Weights)
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对于中文自动语音识别（附加），从 [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), 和 [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) 下载模型，并将它们放置在 `tools/asr/models` 中。
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对于多语言自动语音识别（附加），从 [FunAudioLLM/SenseVoiceSmall](https://huggingface.co/FunAudioLLM/SenseVoiceSmall/tree/main) 或 [iic/SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/files) 下载模型，并将它们放置在 `tools/asr/models` 中。
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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”)
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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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## 数据集格式
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@ -216,16 +210,11 @@ python audio_slicer.py \
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--min_interval <shortest_time_gap_between_adjacent_subclips>
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--hop_size <step_size_for_computing_volume_curve>
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````
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这是使用命令行完成数据集ASR处理的方式（仅限中文）
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这是使用命令行完成数据集ASR处理的方式
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````
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python tools/asr/funasr_asr.py -i <input> -o <output>
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python tools/asr/sensevoice.py -i <input> -o <output> -l <language> -d <device>
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````
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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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启用自定义列表保存路径
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## 致谢
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@ -252,8 +241,7 @@ python ./tools/asr/fasterwhisper_asr.py -i <input> -o <output> -l <language>
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- [SubFix](https://github.com/cronrpc/SubFix)
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- [FFmpeg](https://github.com/FFmpeg/FFmpeg)
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- [gradio](https://github.com/gradio-app/gradio)
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- [faster-whisper](https://github.com/SYSTRAN/faster-whisper)
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- [FunASR](https://github.com/alibaba-damo-academy/FunASR)
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- [SenseVoice](https://github.com/FunAudioLLM/SenseVoice)
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## 感谢所有贡献者的努力
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@ -9,7 +9,7 @@ gradio_client==0.8.1
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ffmpeg-python
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onnxruntime
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tqdm
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funasr==1.0.0
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funasr=1.1.0
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cn2an
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pypinyin
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pyopenjtalk
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@ -24,5 +24,4 @@ psutil
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jieba_fast
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jieba
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LangSegment>=0.2.0
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Faster_Whisper
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wordsegment
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38
webui.py
38
webui.py
@ -202,16 +202,17 @@ def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang):
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cmd += f' -i "{asr_inp_dir}"'
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cmd += f' -o "{asr_opt_dir}"'
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cmd += f' -l {asr_lang}'
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yield "ASR任务开启：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True}
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output_file_name = os.path.basename(asr_inp_dir)
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output_folder = asr_opt_dir or "output/asr_opt"
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output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')
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yield "ASR任务开启：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True},{"__type__":"update"}
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print(cmd)
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p_asr = Popen(cmd, shell=True)
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p_asr.wait()
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p_asr=None
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yield f"ASR任务完成, 查看终端进行下一步",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
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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}
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else:
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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}
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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"}
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# return None
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def close_asr():
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@ -732,7 +733,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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label = i18n("ASR 模型"),
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choices = ['SenseVoice'],
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interactive = True,
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value="enseVoice"
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value="SenseVoice"
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)
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asr_size = gr.Dropdown(
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label = i18n("ASR 模型尺寸"),
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@ -761,7 +762,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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label_info = gr.Textbox(label=i18n("打标工具进程输出信息"))
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if_label.change(change_label, [if_label,path_list], [label_info])
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if_uvr5.change(change_uvr5, [if_uvr5], [uvr5_info])
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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])
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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,path_list])
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close_asr_button.click(close_asr, [], [asr_info,open_asr_button,close_asr_button])
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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])
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close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button])
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@ -869,3 +870,26 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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server_port=webui_port_main,
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quiet=True,
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)
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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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cmd = f'"{python_exec}" tools/asr/{asr_dict[asr_model]["path"]}'
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cmd += f' -i "{asr_inp_dir}"'
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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 += f" -p {asr_precision}"
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yield "ASR任务开启：%s"%cmd,{"__type__":"update","visible":False},{"__type__":"update","visible":True},{"__type__":"update"}
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print(cmd)
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p_asr = Popen(cmd, shell=True)
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p_asr.wait()
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p_asr=None
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yield f"ASR任务完成, 查看终端进行下一步",{"__type__":"update","visible":True},{"__type__":"update","visible":False},
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else:
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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"}
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# return None
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