convert.py:
with torch.no_grad():
for line in tqdm(zip(titles, srcs, tgts)):
title, src, tgt = line
tgt
wav_tgt, _ = librosa.load(tgt, sr=hps.data.sampling_rate)
wav_tgt, _ = librosa.effects.trim(wav_tgt, top_db=20)
对音频会进行静音切除,然后再生成mel谱。但是训练的时候貌似没有做这个操作,是否会导致不匹配呢
convert.py:
with torch.no_grad():
for line in tqdm(zip(titles, srcs, tgts)):
title, src, tgt = line
tgt
wav_tgt, _ = librosa.load(tgt, sr=hps.data.sampling_rate)
wav_tgt, _ = librosa.effects.trim(wav_tgt, top_db=20)
对音频会进行静音切除,然后再生成mel谱。但是训练的时候貌似没有做这个操作,是否会导致不匹配呢