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support ultra-long silence filtering

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This commit is contained in:
boostpapa 2025-04-08 11:23:11 +08:00
parent 397fef2f14
commit 2523001bb4
1 changed files with 47 additions and 4 deletions
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51
indextts/infer.py
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@ -42,6 +42,7 @@ class IndexTTS:
self.bigvgan = self.bigvgan.to(self.device)
self.bigvgan.eval()
print(">> bigvgan weights restored from:", self.bigvgan_path)
self.bpe_path = os.path.join(self.model_dir, self.cfg.dataset['bpe_model'])
self.normalizer = TextNormalizer()
self.normalizer.load()
print(">> TextNormalizer loaded")
@ -57,6 +58,40 @@ class IndexTTS:
# return text.translate(punctuation_map)
return self.normalizer.infer(text)
def remove_long_silence(self, codes):
code_lens = []
for i in range(0, codes.shape[0]):
code = codes[i]
if self.cfg.gpt.stop_mel_token not in code:
code_lens.append(len(code))
len_ = len(code)
else:
# len_ = code.cpu().tolist().index(8193)+1
len_ = (code == self.stop_mel_token).nonzero(as_tuple=False)[0] + 1
len_ = len_ - 2
count = torch.sum(code == 52).item()
if count > 50:
code = code.cpu().tolist()
ncode = []
n = 0
for k in range(0, len_):
if code[k] != 52:
ncode.append(code[k])
n = 0
elif code[k] == 52 and n < 30:
ncode.append(code[k])
n += 1
# if (k == 0 and code[k] == 52) or (code[k] == 52 and code[k-1] == 52):
# n += 1
len_ = len(ncode)
ncode = torch.LongTensor(ncode)
codes[i] = self.stop_mel_token
codes[i, 0:len_] = ncode
code_lens.append(len_)
code_lens = torch.LongTensor(code_lens).cuda()
return codes, code_lens
def infer(self, audio_prompt, text, output_path):
print(f"origin text:{text}")
text = self.preprocess_text(text)
@ -74,7 +109,7 @@ class IndexTTS:
auto_conditioning = cond_mel
tokenizer = spm.SentencePieceProcessor()
tokenizer.load(os.path.join(self.model_dir,self.cfg.dataset['bpe_model']))
tokenizer.load(self.bpe_path)
punctuation = ["!", "?", ".", ";", "！", "？", "。", "；"]
pattern = r"(?<=[{0}])\s*".format("".join(punctuation))
@ -128,15 +163,19 @@ class IndexTTS:
num_beams=num_beams,
repetition_penalty=repetition_penalty,
max_generate_length=max_mel_tokens)
codes = codes[:, :-2]
# code_lens = torch.tensor([codes.shape[-1]])
print(codes)
print(f"codes shape: {codes.shape}")
codes = codes[:, :-2]
# remove ultra-long silence if exits
codes, code_lens = self.remove_long_silence(codes)
print(f"codes shape: {codes.shape}")
# latent, text_lens_out, code_lens_out = \
latent = \
self.gpt(auto_conditioning, text_tokens,
torch.tensor([text_tokens.shape[-1]], device=text_tokens.device), codes,
torch.tensor([codes.shape[-1] * self.gpt.mel_length_compression], device=text_tokens.device),
code_lens*self.gpt.mel_length_compression,
cond_mel_lengths=torch.tensor([auto_conditioning.shape[-1]], device=text_tokens.device),
return_latent=True, clip_inputs=False)
latent = latent.transpose(1, 2)
@ -162,6 +201,10 @@ class IndexTTS:
torchaudio.save(output_path, wav.type(torch.int16), 24000)
prompt_wav="/juicefs/users/wd007/work2024/tts/indextts/testwav/spk_1743041132.wav"
text="晕 XUAN4 是 一 种 GAN3 觉"
text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！'
if __name__ == "__main__":
tts = IndexTTS(cfg_path="checkpoints/config.yaml", model_dir="checkpoints")
tts.infer(audio_prompt='test_data/input.wav', text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！', output_path="gen.wav")
#tts.infer(audio_prompt='test_data/input.wav', text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！', output_path="gen.wav")
tts.infer(audio_prompt=prompt_wav, text=text, output_path="gen.wav")