NtTestAlert/tortoise-tts
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Add support for multiple output candidates in do_tts.

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James Betker 2022-05-12 11:25:35 -06:00
parent 33d4226a7d
commit fc7b308e3b
1 changed files with 7 additions and 2 deletions
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7
tortoise/do_tts.py
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@ -18,6 +18,7 @@ if __name__ == '__main__':
parser.add_argument('--output_path', type=str, help='Where to store outputs.', default='results/') parser.add_argument('--output_path', type=str, help='Where to store outputs.', default='results/')
parser.add_argument('--model_dir', type=str, help='Where to find pretrained model checkpoints. Tortoise automatically downloads these to .models, so this' parser.add_argument('--model_dir', type=str, help='Where to find pretrained model checkpoints. Tortoise automatically downloads these to .models, so this'
'should only be specified if you have custom checkpoints.', default='.models') 'should only be specified if you have custom checkpoints.', default='.models')
parser.add_argument('--candidates', type=int, help='How many output candidates to produce per-voice.', default=3)
args = parser.parse_args() args = parser.parse_args()
os.makedirs(args.output_path, exist_ok=True) os.makedirs(args.output_path, exist_ok=True)
@ -26,7 +27,11 @@ if __name__ == '__main__':
selected_voices = args.voice.split(',') selected_voices = args.voice.split(',')
for k, voice in enumerate(selected_voices): for k, voice in enumerate(selected_voices):
voice_samples, conditioning_latents = load_voice(voice) voice_samples, conditioning_latents = load_voice(voice)
gen = tts.tts_with_preset(args.text, voice_samples=voice_samples, conditioning_latents=conditioning_latents, gen = tts.tts_with_preset(args.text, k=args.candidates, voice_samples=voice_samples, conditioning_latents=conditioning_latents,
preset=args.preset, clvp_cvvp_slider=args.voice_diversity_intelligibility_slider) preset=args.preset, clvp_cvvp_slider=args.voice_diversity_intelligibility_slider)
if isinstance(gen, list):
for j, g in enumerate(gen):
torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}_{j}.wav'), g.squeeze(0).cpu(), 24000)
else:
torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}.wav'), gen.squeeze(0).cpu(), 24000) torchaudio.save(os.path.join(args.output_path, f'{voice}_{k}.wav'), gen.squeeze(0).cpu(), 24000)