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import os
from random import shuffle
import torchaudio
from api import TextToSpeech
from utils.audio import load_audio
def permutations(args):
res = []
k = next(iter(args.keys()))
vals = args[k]
del args[k]
if not args:
return [{k: v} for v in vals]
lower = permutations(args)
for v in vals:
for l in lower:
lc = l.copy()
lc[k] = v
res.append(lc)
return res
if __name__ == '__main__':
fname = 'Y:\\clips\\books2\\subset512-oco.tsv'
stop_after = 512
outpath_base = 'D:\\tmp\\tortoise-tts-eval\\sweep-2'
outpath_real = 'D:\\tmp\\tortoise-tts-eval\\real'
arg_ranges = {
'top_p': [.8,1],
'temperature': [.8,.9,1],
'diffusion_temperature': [.8,1],
'cond_free_k': [1,2,5,10],
}
cfgs = permutations(arg_ranges)
shuffle(cfgs)
for cfg in cfgs:
cfg_desc = '_'.join([f'{k}-{v}' for k,v in cfg.items()])
outpath = os.path.join(outpath_base, f'{cfg_desc}')
os.makedirs(outpath, exist_ok=True)
os.makedirs(outpath_real, exist_ok=True)
with open(fname, 'r', encoding='utf-8') as f:
lines = [l.strip().split('\t') for l in f.readlines()]
recorder = open(os.path.join(outpath, 'transcript.tsv'), 'w', encoding='utf-8')
tts = TextToSpeech()
for e, line in enumerate(lines):
if e >= stop_after:
break
transcript = line[0]
path = os.path.join(os.path.dirname(fname), line[1])
cond_audio = load_audio(path, 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=32, repetition_penalty=2.0,
k=1, diffusion_iterations=32, length_penalty=1.0, **cfg)
down = torchaudio.functional.resample(sample, 24000, 22050)
fout_path = os.path.join(outpath, os.path.basename(line[1]))
torchaudio.save(fout_path, down.squeeze(0), 22050)
recorder.write(f'{transcript}\t{fout_path}\n')
recorder.flush()
recorder.close() |