| | |
|---|
| | | if whisper_model == "large-v3" or whisper_model == "large": |
|---|
| | | self.n_mels = 128 |
|---|
| | | |
|---|
| | | self.mel_filters = whisper.audio.mel_filters |
|---|
| | | filters_path = kwargs.get("filters_path", None) |
|---|
| | | self.filters_path = filters_path |
|---|
| | | if filters_path is not None: |
|---|
| | | from funasr.models.sense_voice.whisper_lib.audio import mel_filters |
|---|
| | | self.mel_filters = mel_filters |
|---|
| | | else: |
|---|
| | | self.mel_filters = whisper.audio.mel_filters |
|---|
| | | self.do_pad_trim = do_pad_trim |
|---|
| | | if do_pad_trim: |
|---|
| | | self.pad_or_trim = whisper.pad_or_trim |
|---|
| | |
|---|
| | | |
|---|
| | | # whisper deletes the last frame by default (Shih-Lun) |
|---|
| | | magnitudes = stft[..., :-1].abs() ** 2 |
|---|
| | | |
|---|
| | | filters = self.mel_filters(audio.device, self.n_mels) |
|---|
| | | if self.filters_path is not None: |
|---|
| | | filters = self.mel_filters(audio.device, self.n_mels, self.filters_path) |
|---|
| | | else: |
|---|
| | | filters = self.mel_filters(audio.device, self.n_mels) |
|---|
| | | mel_spec = filters @ magnitudes |
|---|
| | | |
|---|
| | | log_spec = torch.clamp(mel_spec, min=1e-10).log10() |
|---|
| | |
|---|
| | | batch_size = input.size(0) |
|---|
| | | feats = [] |
|---|
| | | feats_lens = [] |
|---|
| | | input = input.to(torch.float32) |
|---|
| | | for i in range(batch_size): |
|---|
| | | if self.do_pad_trim: |
|---|
| | | feat = self.pad_or_trim(input[i], self.pad_samples) |
|---|
