tuna2134/sbv2-v2
1
0
Fork 0
Code Issues Pull Requests 1 Actions Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
rcell
2023-07-22 08:17:25 +08:00
parent abac0cb146
commit 8fc674fe2c
8 changed files with 50264 additions and 249 deletions
Download Patch File Download Diff File Expand all files Collapse all files

30
data_utils.py
View File

@@ -8,7 +8,7 @@ import torch.utils.data
import commons
from mel_processing import spectrogram_torch
from utils import load_wav_to_torch, load_filepaths_and_text
from text import cleaned_text_to_sequence, cleaned_text_to_sequence_bert, get_bert
from text import cleaned_text_to_sequence, get_bert
"""Multi speaker version"""
class TextAudioSpeakerLoader(torch.utils.data.Dataset):
@@ -66,7 +66,7 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
# separate filename, speaker_id and text
audiopath, sid, language, text, phones, tone, word2ph = audiopath_sid_text
bert, phones, tone, language = self.get_text(text, word2ph, phones, tone, language)
bert, phones, tone, language = self.get_text(text, word2ph, phones, tone, language,audiopath)
spec, wav = self.get_audio(audiopath)
sid = torch.LongTensor([int(self.spk_map[sid])])
@@ -90,15 +90,33 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
torch.save(spec, spec_filename)
return spec, audio_norm
def get_text(self,text, word2ph,phone, tone, language_str):
def get_text(self,text, word2ph,phone, tone, language_str, wav_path):
# print(text, word2ph,phone, tone, language_str)
pold = phone
w2pho = [i for i in word2ph]
word2ph = [i for i in word2ph]
phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
pold2 = phone
if self.add_blank:
p1 = len(phone)
phone = commons.intersperse(phone, 0)
p2 = len(phone)
t1 = len(tone)
tone = commons.intersperse(tone, 0)
t2 = len(tone)
language = commons.intersperse(language, 0)
for i in range(1,len(word2ph)):
word2ph[i] += 1
bert = get_bert(text, word2ph, language_str)
for i in range(len(word2ph)):
word2ph[i] = word2ph[i] * 2
word2ph[0] += 1
bert_path = wav_path.replace(".wav", ".bert.pt")
try:
bert = torch.load(bert_path)
assert bert.shape[-1] == len(phone)
except:
bert = get_bert(text, word2ph, language_str)
assert bert.shape[-1] == len(phone), (bert.shape, len(phone), sum(word2ph), p1, p2, t1, t2, pold, pold2,word2ph, text,w2pho)
torch.save(bert, bert_path)
phone = torch.LongTensor(phone)
tone = torch.LongTensor(tone)
language = torch.LongTensor(language)