mirror of https://github.com/coqui-ai/TTS.git
3c2d5a9e03
* chore: remove unused argument * refactor(audio.processor): remove duplicate stft+griffin_lim * chore(audio.processor): remove unused compute_stft_paddings Same function available in numpy_transforms * refactor(audio.processor): remove duplicate db_to_amp * refactor(audio.processor): remove duplicate amp_to_db * refactor(audio.processor): remove duplicate linear_to_mel * refactor(audio.processor): remove duplicate mel_to_linear * refactor(audio.processor): remove duplicate build_mel_basis * refactor(audio.processor): remove duplicate stft_parameters * refactor(audio.processor): use pre-/deemphasis from numpy_transforms * refactor(audio.processor): use rms_volume_norm from numpy_transforms * chore(audio.processor): remove duplicate assert Already checked in numpy_transforms.compute_f0 * refactor(audio.processor): use find_endpoint from numpy_transforms * refactor(audio.processor): use trim_silence from numpy_transforms * refactor(audio.processor): use volume_norm from numpy_transforms * refactor(audio.processor): use load_wav from numpy_transforms * fix(bin.extract_tts_spectrograms): set quantization bits * fix(ExtractTTSpectrogram.ipynb): adapt to current TTS code Fixes #2447, #2574 * refactor(audio.processor): remove duplicate quantization methods |
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.. | ||
dataset_analysis | ||
ExtractTTSpectrogram.ipynb | ||
PlotUmapLibriTTS.ipynb | ||
TestAttention.ipynb | ||
Tortoise.ipynb | ||
Tutorial_1_use-pretrained-TTS.ipynb | ||
Tutorial_2_train_your_first_TTS_model.ipynb |