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https://github.com/OpenBMB/VoxCPM
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Update: default no denoise & normalize
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12
README.md
12
README.md
@@ -76,7 +76,7 @@ By default, when you first run the script, the model will be downloaded automati
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from huggingface_hub import snapshot_download
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snapshot_download("openbmb/VoxCPM-0.5B")
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```
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- Download ZipEnhancer and SenseVoice-Small. We use ZipEnhancer to enhance speech prompts and SenseVoice-Small for speech prompt ASR in the web demo.
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- Download ZipEnhancer and SenseVoice-Small. We use ZipEnhancer to enhance speech prompts and SenseVoice-Small for speech prompt ASR in the web demo.
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```
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from modelscope import snapshot_download
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snapshot_download('iic/speech_zipenhancer_ans_multiloss_16k_base')
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@@ -98,8 +98,8 @@ wav = model.generate(
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prompt_text=None, # optional: reference text
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cfg_value=2.0, # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse
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inference_timesteps=10, # LocDiT inference timesteps, higher for better result, lower for fast speed
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normalize=True, # enable external TN tool, but will disable native raw text support
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denoise=True, # enable external Denoise tool, but it may cause some distortion and restrict the sampling rate to 16kHz
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normalize=False, # enable external TN tool, but will disable native raw text support
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denoise=False, # enable external Denoise tool, but it may cause some distortion and restrict the sampling rate to 16kHz
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retry_badcase=True, # enable retrying mode for some bad cases (unstoppable)
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retry_badcase_max_times=3, # maximum retrying times
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retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech
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@@ -134,14 +134,14 @@ voxcpm --text "VoxCPM is an innovative end-to-end TTS model from ModelBest, desi
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--prompt-audio path/to/voice.wav \
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--prompt-text "reference transcript" \
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--output out.wav \
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--denoise
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# --denoise
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# (Optinal) Voice cloning (reference audio + transcript file)
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voxcpm --text "VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech." \
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--prompt-audio path/to/voice.wav \
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--prompt-file "/path/to/text-file" \
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--output out.wav \
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--denoise
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# --denoise
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# 3) Batch processing (one text per line)
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voxcpm --input examples/input.txt --output-dir outs
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@@ -149,7 +149,7 @@ voxcpm --input examples/input.txt --output-dir outs
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voxcpm --input examples/input.txt --output-dir outs \
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--prompt-audio path/to/voice.wav \
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--prompt-text "reference transcript" \
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--denoise
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# --denoise
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# 4) Inference parameters (quality/speed)
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voxcpm --text "..." --output out.wav \
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