Merge branch 'develop' of github.com:SmileGoat/PaddleSpeech into add_fbank

examples/other/mfa/local/reorganize_aishell3.py

@@ -46,22 +46,22 @@ def write_lab(root_dir: Union[str, Path],
         text_path = root_dir / sub_set / 'content.txt'
         new_dir = output_dir / sub_set
 
-    with open(text_path, 'r') as rf:
-        for line in rf:
-            wav_id, context = line.strip().split('\t')
-            spk_id = wav_id[:7]
-            transcript_name = wav_id.split('.')[0] + '.lab'
-            transcript_path = new_dir / spk_id / transcript_name
-            context_list = context.split()
-            word_list = context_list[0:-1:2]
-            pinyin_list = context_list[1::2]
-            wf = open(transcript_path, 'w')
-            if script_type == 'word':
-                # add space between chinese char
-                new_context = ' '.join(word_list)
-            elif script_type == 'pinyin':
-                new_context = ' '.join(pinyin_list)
-            wf.write(new_context + '\n')
+        with open(text_path, 'r') as rf:
+            for line in rf:
+                wav_id, context = line.strip().split('\t')
+                spk_id = wav_id[:7]
+                transcript_name = wav_id.split('.')[0] + '.lab'
+                transcript_path = new_dir / spk_id / transcript_name
+                context_list = context.split()
+                word_list = context_list[0:-1:2]
+                pinyin_list = context_list[1::2]
+                wf = open(transcript_path, 'w')
+                if script_type == 'word':
+                    # add space between chinese char
+                    new_context = ' '.join(word_list)
+                elif script_type == 'pinyin':
+                    new_context = ' '.join(pinyin_list)
+                wf.write(new_context + '\n')
 
 
 def reorganize_aishell3(root_dir: Union[str, Path],

paddlespeech/t2s/exps/voice_cloning.py

@@ -110,10 +110,10 @@ def voice_cloning(args):
         print(f"{utt_id} done!")
     # Randomly generate numbers of 0 ~ 0.2, 256 is the dim of spk_emb
     random_spk_emb = np.random.rand(256) * 0.2
-    random_spk_emb = paddle.to_tensor(random_spk_emb)
+    random_spk_emb = paddle.to_tensor(random_spk_emb, dtype='float32')
     utt_id = "random_spk_emb"
     with paddle.no_grad():
-        wav = voc_inference(am_inference(phone_ids, spk_emb=spk_emb))
+        wav = voc_inference(am_inference(phone_ids, spk_emb=random_spk_emb))
     sf.write(
         str(output_dir / (utt_id + ".wav")),
         wav.numpy(),