forked from mrq/tortoise-tts
76 lines
3.0 KiB
Python
76 lines
3.0 KiB
Python
import argparse
|
|
import os
|
|
|
|
import torch
|
|
import torch.nn.functional as F
|
|
import torchaudio
|
|
|
|
from api import TextToSpeech, load_conditioning
|
|
from utils.audio import load_audio, get_voices
|
|
from utils.tokenizer import VoiceBpeTokenizer
|
|
|
|
def split_and_recombine_text(texts, desired_length=200, max_len=300):
|
|
# TODO: also split across '!' and '?'. Attempt to keep quotations together.
|
|
texts = [s.strip() + "." for s in texts.split('.')]
|
|
|
|
i = 0
|
|
while i < len(texts):
|
|
ltxt = texts[i]
|
|
if len(ltxt) >= desired_length or i == len(texts)-1:
|
|
i += 1
|
|
continue
|
|
if len(ltxt) + len(texts[i+1]) > max_len:
|
|
i += 1
|
|
continue
|
|
texts[i] = f'{ltxt} {texts[i+1]}'
|
|
texts.pop(i+1)
|
|
return texts
|
|
|
|
if __name__ == '__main__':
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument('--textfile', type=str, help='A file containing the text to read.', default="data/riding_hood2.txt")
|
|
parser.add_argument('--voice', type=str, help='Selects the voice to use for generation. See options in voices/ directory (and add your own!) '
|
|
'Use the & character to join two voices together. Use a comma to perform inference on multiple voices.', default='patrick_stewart')
|
|
parser.add_argument('--output_path', type=str, help='Where to store outputs.', default='results/longform/')
|
|
parser.add_argument('--generation_preset', type=str, help='Preset to use for generation', default='standard')
|
|
args = parser.parse_args()
|
|
|
|
outpath = args.output_path
|
|
voices = get_voices()
|
|
selected_voices = args.voice.split(',')
|
|
for selected_voice in selected_voices:
|
|
voice_outpath = os.path.join(outpath, selected_voice)
|
|
os.makedirs(voice_outpath, exist_ok=True)
|
|
|
|
with open(args.textfile, 'r', encoding='utf-8') as f:
|
|
text = ''.join([l for l in f.readlines()])
|
|
texts = split_and_recombine_text(text)
|
|
tts = TextToSpeech()
|
|
|
|
if '&' in selected_voice:
|
|
voice_sel = selected_voice.split('&')
|
|
else:
|
|
voice_sel = [selected_voice]
|
|
cond_paths = []
|
|
for vsel in voice_sel:
|
|
if vsel not in voices.keys():
|
|
print(f'Error: voice {vsel} not available. Skipping.')
|
|
continue
|
|
cond_paths.extend(voices[vsel])
|
|
if not cond_paths:
|
|
print('Error: no valid voices specified. Try again.')
|
|
|
|
priors = []
|
|
for j, text in enumerate(texts):
|
|
conds = priors.copy()
|
|
for cond_path in cond_paths:
|
|
c = load_audio(cond_path, 22050)
|
|
conds.append(c)
|
|
gen = tts.tts_with_preset(text, conds, preset=args.generation_preset)
|
|
torchaudio.save(os.path.join(voice_outpath, f'{j}.wav'), gen.squeeze(0).cpu(), 24000)
|
|
|
|
priors.append(torchaudio.functional.resample(gen, 24000, 22050).squeeze(0))
|
|
while len(priors) > 2:
|
|
priors.pop(0)
|
|
|