fix

Author: innnky

convert.py

@@ -54,7 +54,7 @@ def get_audio(self, filename):
             spec = torch.squeeze(spec, 0)
             torch.save(spec, spec_filename)
 
-        spk = filename.split("/")[-2]
+        spk = filename.split(os.sep)[-2]
         spk = torch.LongTensor([self.spk_map[spk]])
 
         c = torch.load(filename + ".soft.pt").squeeze(0)
@@ -106,7 +106,7 @@ def __init__(self, audiopaths, hparams):
         self.win_length = hparams.data.win_length
         self.sampling_rate = hparams.data.sampling_rate
         self.use_sr = hparams.train.use_sr
-        self.audiopaths = self.audiopaths[:10]
+        self.audiopaths = self.audiopaths[:5]
         self.spk_map = hparams.spk
 
 
@@ -127,7 +127,7 @@ def get_audio(self, filename):
             spec = torch.squeeze(spec, 0)
             torch.save(spec, spec_filename)
 
-        spk = filename.split("/")[-2]
+        spk = filename.split(os.sep)[-2]
         spk = torch.LongTensor([self.spk_map[spk]])
 
         c = torch.load(filename + ".soft.pt").squeeze(0)

convert.txt

@@ -21,8 +21,8 @@
 
 # 支持多个wav文件，放在raw文件夹下
 clean_names = ["君の知らない物語-src"]
-trans = [-3]  # 音高调整，支持正负（半音）
-spk_list = ['paimon']  # 每次同时合成多语者音色
+trans = [-5]  # 音高调整，支持正负（半音）
+spk_list = ['yunhao']  # 每次同时合成多语者音色
 slice_db = -40  # 默认-40，嘈杂的音频可以-30，干声保留呼吸可以-50
 wav_format = 'flac'  # 音频输出格式
 

data_utils.py

@@ -10,7 +10,7 @@
 def process(item):
     spkdir, wav_name, args = item
     # speaker 's5', 'p280', 'p315' are excluded,
-    speaker = spkdir.split("/")[-1]
+    speaker = spkdir.split(os.sep)[-1]
     wav_path = os.path.join(args.in_dir, speaker, wav_name)
     if os.path.exists(wav_path) and '.wav' in wav_path:
         os.makedirs(os.path.join(args.out_dir2, speaker), exist_ok=True)

inference_main.py

@@ -113,7 +113,7 @@ def load_checkpoint(checkpoint_path, model, optimizer=None):
 
 
 def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
-  # ckptname = checkpoint_path.split("/")[-1]
+  # ckptname = checkpoint_path.split(os.sep)[-1]
   # newest_step = int(ckptname.split(".")[0].split("_")[1])
   # val_steps = 2000
   # last_ckptname = checkpoint_path.replace(str(newest_step), str(newest_step - val_steps*3))