NtTestAlert/tortoise-tts
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James Betker 2022-04-12 16:40:42 -06:00
parent 31cb602e07
commit 5988aa34eb
2 changed files with 4 additions and 4 deletions
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2
api.py
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@ -138,7 +138,7 @@ class TextToSpeech:
heads=16, number_text_tokens=256, start_text_token=255, checkpointing=False, heads=16, number_text_tokens=256, start_text_token=255, checkpointing=False,
train_solo_embeddings=False, train_solo_embeddings=False,
average_conditioning_embeddings=True).cpu().eval() average_conditioning_embeddings=True).cpu().eval()
self.autoregressive.load_state_dict(torch.load('.models/autoregressive.pth')) self.autoregressive.load_state_dict(torch.load('.models/autoregressive_diverse.pth'))
self.clip = VoiceCLIP(dim_text=512, dim_speech=512, dim_latent=512, num_text_tokens=256, text_enc_depth=12, self.clip = VoiceCLIP(dim_text=512, dim_speech=512, dim_latent=512, num_text_tokens=256, text_enc_depth=12,
text_seq_len=350, text_heads=8, text_seq_len=350, text_heads=8,

6
eval_multiple.py
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@ -7,7 +7,7 @@ from utils.audio import load_audio
if __name__ == '__main__': if __name__ == '__main__':
fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv' fname = 'Y:\\libritts\\test-clean\\transcribed-brief-w2v.tsv'
outpath = 'D:\\tmp\\tortoise-tts-eval\\eval_new_autoregressive' outpath = 'D:\\tmp\\tortoise-tts-eval\\diverse_auto_256_samp_100_di_4'
outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real' outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
os.makedirs(outpath, exist_ok=True) os.makedirs(outpath, exist_ok=True)
@ -24,9 +24,9 @@ if __name__ == '__main__':
path = os.path.join(os.path.dirname(fname), line[1]) path = os.path.join(os.path.dirname(fname), line[1])
cond_audio = load_audio(path, 22050) cond_audio = load_audio(path, 22050)
torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050) torchaudio.save(os.path.join(outpath_real, os.path.basename(line[1])), cond_audio, 22050)
sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=512, k=1, sample = tts.tts(transcript, [cond_audio, cond_audio], num_autoregressive_samples=256, k=1,
repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5, repetition_penalty=2.0, length_penalty=2, temperature=.5, top_p=.5,
diffusion_temperature=.7, cond_free_k=2, diffusion_iterations=200) diffusion_temperature=.7, cond_free_k=2, diffusion_iterations=100)
down = torchaudio.functional.resample(sample, 24000, 22050) down = torchaudio.functional.resample(sample, 24000, 22050)
fout_path = os.path.join(outpath, os.path.basename(line[1])) fout_path = os.path.join(outpath, os.path.basename(line[1]))