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@ -87,8 +87,18 @@
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2-引入paddlespeech的Normalizer https://github.com/RVC-Boss/GPT-SoVITS/pull/377 修复一些问题，例如：xx.xx%(带百分号类)，元/吨 会读成 元吨 而不是元每吨,下划线不再会报错
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### 20240207更新
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1-修正语种传参混乱导致中文推理效果下降 https://github.com/RVC-Boss/GPT-SoVITS/issues/391
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2-uvr5适配高版本librosa https://github.com/RVC-Boss/GPT-SoVITS/pull/403
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3-修复uvr5 inf everywhere报错的问题(is_half传参未转换bool导致恒定半精度推理，16系显卡会inf) https://github.com/RVC-Boss/GPT-SoVITS/commit/14a285109a521679f8846589c22da8f656a46ad8
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todolist：
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1-中文多音字推理优化
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2-测试集成faster whisper ASR日文英文
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@ -1,26 +1,27 @@
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numpy
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scipy
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tensorboard
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librosa==0.9.2
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numba==0.56.4
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pytorch-lightning
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gradio==3.38.0
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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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cn2an
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pypinyin
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pyopenjtalk
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g2p_en
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torchaudio
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modelscope==1.10.0
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sentencepiece
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transformers
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chardet
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PyYAML
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psutil
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jieba_fast
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jieba
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LangSegment
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Faster_Whisper
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numpy
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scipy
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tensorboard
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librosa==0.9.2
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numba==0.56.4
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pytorch-lightning
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gradio==3.38.0
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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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cn2an
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pypinyin
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pyopenjtalk
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g2p_en
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torchaudio
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modelscope==1.10.0
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sentencepiece
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transformers
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chardet
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PyYAML
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psutil
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jieba_fast
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jieba
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LangSegment
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Faster_Whisper
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@ -43,8 +43,8 @@ def wave_to_spectrogram(
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wave_left = np.asfortranarray(wave[0])
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wave_right = np.asfortranarray(wave[1])
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spec_left = librosa.stft(wave_left, n_fft, hop_length=hop_length)
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spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
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spec_left = librosa.stft(wave_left, n_fft=n_fft, hop_length=hop_length)
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spec_right = librosa.stft(wave_right, n_fft=n_fft, hop_length=hop_length)
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spec = np.asfortranarray([spec_left, spec_right])
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@ -78,7 +78,7 @@ def wave_to_spectrogram_mt(
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kwargs={"y": wave_left, "n_fft": n_fft, "hop_length": hop_length},
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)
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thread.start()
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spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
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spec_right = librosa.stft(wave_right, n_fft=n_fft, hop_length=hop_length)
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thread.join()
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spec = np.asfortranarray([spec_left, spec_right])
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@ -230,27 +230,31 @@ def cache_or_load(mix_path, inst_path, mp):
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if d == len(mp.param["band"]): # high-end band
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X_wave[d], _ = librosa.load(
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mix_path, bp["sr"], False, dtype=np.float32, res_type=bp["res_type"]
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mix_path,
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"]
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)
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y_wave[d], _ = librosa.load(
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inst_path,
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bp["sr"],
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False,
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dtype=np.float32,
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res_type=bp["res_type"],
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"],
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)
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else: # lower bands
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X_wave[d] = librosa.resample(
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X_wave[d + 1],
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mp.param["band"][d + 1]["sr"],
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bp["sr"],
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res_type=bp["res_type"],
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orig_sr = mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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y_wave[d] = librosa.resample(
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y_wave[d + 1],
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mp.param["band"][d + 1]["sr"],
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bp["sr"],
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res_type=bp["res_type"],
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orig_sr = mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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X_wave[d], y_wave[d] = align_wave_head_and_tail(X_wave[d], y_wave[d])
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@ -401,9 +405,9 @@ def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None):
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mp.param["mid_side_b2"],
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mp.param["reverse"],
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),
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bp["sr"],
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sr,
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res_type="sinc_fastest",
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orig_sr = bp["sr"],
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target_sr = sr,
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res_type = "sinc_fastest",
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)
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else: # mid
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spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
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@ -418,8 +422,8 @@ def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None):
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mp.param["reverse"],
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),
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)
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# wave = librosa.core.resample(wave2, bp['sr'], sr, res_type="sinc_fastest")
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wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="scipy")
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# wave = librosa.core.resample(wave2, orig_sr=bp['sr'], target_sr=sr, res_type="sinc_fastest")
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wave = librosa.core.resample(wave2, orig_sr=bp["sr"], target_sr=sr, res_type="scipy")
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return wave.T
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@ -506,8 +510,8 @@ def ensembling(a, specs):
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def stft(wave, nfft, hl):
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wave_left = np.asfortranarray(wave[0])
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wave_right = np.asfortranarray(wave[1])
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spec_left = librosa.stft(wave_left, nfft, hop_length=hl)
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spec_right = librosa.stft(wave_right, nfft, hop_length=hl)
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spec_left = librosa.stft(wave_left, n_fft=nfft, hop_length=hl)
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spec_right = librosa.stft(wave_right, n_fft=nfft, hop_length=hl)
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spec = np.asfortranarray([spec_left, spec_right])
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return spec
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@ -569,10 +573,10 @@ if __name__ == "__main__":
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if d == len(mp.param["band"]): # high-end band
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wave[d], _ = librosa.load(
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args.input[i],
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bp["sr"],
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False,
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dtype=np.float32,
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res_type=bp["res_type"],
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"],
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)
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if len(wave[d].shape) == 1: # mono to stereo
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@ -580,9 +584,9 @@ if __name__ == "__main__":
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else: # lower bands
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wave[d] = librosa.resample(
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wave[d + 1],
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mp.param["band"][d + 1]["sr"],
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bp["sr"],
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res_type=bp["res_type"],
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orig_sr = mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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spec[d] = wave_to_spectrogram(
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@ -61,19 +61,19 @@ class AudioPre:
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_,
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) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
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music_file,
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bp["sr"],
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False,
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dtype=np.float32,
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res_type=bp["res_type"],
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"],
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)
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if X_wave[d].ndim == 1:
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X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
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else: # lower bands
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X_wave[d] = librosa.core.resample(
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X_wave[d + 1],
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self.mp.param["band"][d + 1]["sr"],
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bp["sr"],
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res_type=bp["res_type"],
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orig_sr = self.mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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# Stft of wave source
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X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
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@ -245,19 +245,19 @@ class AudioPreDeEcho:
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_,
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) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
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music_file,
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bp["sr"],
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False,
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dtype=np.float32,
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res_type=bp["res_type"],
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sr = bp["sr"],
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mono = False,
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dtype = np.float32,
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res_type = bp["res_type"],
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)
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if X_wave[d].ndim == 1:
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X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
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else: # lower bands
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X_wave[d] = librosa.core.resample(
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X_wave[d + 1],
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self.mp.param["band"][d + 1]["sr"],
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bp["sr"],
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res_type=bp["res_type"],
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orig_sr = self.mp.param["band"][d + 1]["sr"],
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target_sr = bp["sr"],
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res_type = bp["res_type"],
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)
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# Stft of wave source
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X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
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@ -19,7 +19,7 @@ for name in os.listdir(weight_uvr5_root):
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uvr5_names.append(name.replace(".pth", ""))
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device=sys.argv[1]
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is_half=sys.argv[2]
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is_half=eval(sys.argv[2])
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webui_port_uvr5=int(sys.argv[3])
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is_share=eval(sys.argv[4])
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