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tacotron2
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Code Issues Releases Wiki Activity

1. fix synth_speech_fast interface 

2. rename private methods
master
Malar 2019-11-28 18:07:47 +05:30
parent ea11c5199e
commit 5efb1e2758
1 changed files with 20 additions and 28 deletions
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48
taco2/tts.py
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@ -17,7 +17,7 @@ from .audio_processing import griffin_lim, postprocess_audio
OUTPUT_SAMPLE_RATE = 22050
GL_ITERS = 30
VOCODER_MODEL = "wavglow"
VOCODER_WAVEGLOW, VOCODER_GL = "wavglow", "gl"
# config from
# https://github.com/NVIDIA/waveglow/blob/master/config.json
@ -74,11 +74,11 @@ class TTSModel(object):
self.waveglow, n_mel_channels=hparams.n_mel_channels
)
self.synth_speech = klepto.safe.inf_cache(cache=self.k_cache)(
self.synth_speech
self._synth_speech
)
else:
self.synth_speech = klepto.safe.inf_cache(cache=self.k_cache)(
self.synth_speech_fast
self._synth_speech_fast
)
self.taco_stft = TacotronSTFT(
hparams.filter_length,
@ -89,7 +89,7 @@ class TTSModel(object):
mel_fmax=4000,
)
def generate_mel_postnet(self, text):
def _generate_mel_postnet(self, text):
sequence = np.array(text_to_sequence(text, ["english_cleaners"]))[None, :]
if torch.cuda.is_available():
sequence = torch.autograd.Variable(torch.from_numpy(sequence)).cuda().long()
@ -102,14 +102,14 @@ class TTSModel(object):
return mel_outputs_postnet
def synth_speech_array(self, text, vocoder):
mel_outputs_postnet = self.generate_mel_postnet(text)
mel_outputs_postnet = self._generate_mel_postnet(text)
if vocoder == "wavglow":
if vocoder == VOCODER_WAVEGLOW:
with torch.no_grad():
audio_t = self.waveglow.infer(mel_outputs_postnet, sigma=0.666)
audio_t = self.denoiser(audio_t, 0.1)[0]
audio = audio_t[0].data
elif vocoder == "gl":
elif vocoder == VOCODER_GL:
mel_decompress = self.taco_stft.spectral_de_normalize(mel_outputs_postnet)
mel_decompress = mel_decompress.transpose(1, 2).data.cpu()
spec_from_mel_scaling = 1000
@ -122,7 +122,7 @@ class TTSModel(object):
audio = griffin_lim(
torch.autograd.Variable(spec_from_mel[:, :, :-1]),
self.taco_stft.stft_fn,
60,
GL_ITERS,
)
audio = audio.squeeze()
else:
@ -130,36 +130,28 @@ class TTSModel(object):
audio = audio.cpu().numpy()
return audio
def synth_speech(
def _synth_speech(
self, text, speed: float = 1.0, sample_rate: int = OUTPUT_SAMPLE_RATE
):
audio = self.synth_speech_array(text, VOCODER_MODEL)
audio = self.synth_speech_array(text, VOCODER_WAVEGLOW)
return postprocess_audio(
audio, src_rate=self.hparams.sampling_rate, dst_rate=sample_rate, tempo=speed
audio,
src_rate=self.hparams.sampling_rate,
dst_rate=sample_rate,
tempo=speed,
)
def synth_speech_fast(
def _synth_speech_fast(
self, text, speed: float = 1.0, sample_rate: int = OUTPUT_SAMPLE_RATE
):
mel_outputs_postnet = self.generate_mel_postnet(text)
mel_decompress = self.taco_stft.spectral_de_normalize(mel_outputs_postnet)
mel_decompress = mel_decompress.transpose(1, 2).data.cpu()
spec_from_mel_scaling = 1000
spec_from_mel = torch.mm(mel_decompress[0], self.taco_stft.mel_basis)
spec_from_mel = spec_from_mel.transpose(0, 1).unsqueeze(0)
spec_from_mel = spec_from_mel * spec_from_mel_scaling
audio = griffin_lim(
torch.autograd.Variable(spec_from_mel[:, :, :-1]),
self.taco_stft.stft_fn,
GL_ITERS,
)
audio = audio.squeeze()
audio = audio.cpu().numpy()
audio = self.synth_speech_array(text, VOCODER_GL)
return postprocess_audio(
audio, tempo=speed, src_rate=self.hparams.sampling_rate, dst_rate=sample_rate
audio,
tempo=speed,
src_rate=self.hparams.sampling_rate,
dst_rate=sample_rate,
)