fix merge_sentences bug

examples/fastspeech2/baker/frontend.py

@@ -48,9 +48,7 @@ class Frontend():
         tone_ids = [self.vocab_tones[item] for item in tones]
         return np.array(tone_ids, np.int64)
 
-    def get_input_ids(self, sentence, get_tone_ids=False):
-        phonemes = self.frontend.get_phonemes(sentence)
-        result = {}
+    def _get_phone_tone(self, phonemes, get_tone_ids=False):
         phones = []
         tones = []
         if get_tone_ids and self.vocab_tones:
@@ -76,12 +74,7 @@ class Frontend():
                 else:
                     phones.append(full_phone)
                     tones.append('0')
-            tone_ids = self._t2id(tones)
-            tone_ids = paddle.to_tensor(tone_ids)
-            result["tone_ids"] = tone_ids
         else:
-
-            phones = []
             for phone in phonemes:
                 # if the merged erhua not in the vocab
                 # assume that the input is ['iaor3'] and 'iaor' not in self.vocab_phones, change ['iaor3'] to ['iao3','er2']
@@ -92,8 +85,30 @@ class Frontend():
                     phones.append("er2")
                 else:
                     phones.append(phone)
+        return phones, tones
 
+    def get_input_ids(self, sentence, merge_sentences=True,
+                      get_tone_ids=False):
+        phonemes = self.frontend.get_phonemes(
+            sentence, merge_sentences=merge_sentences)
+        result = {}
+        phones = []
+        tones = []
+        temp_phone_ids = []
+        temp_tone_ids = []
+        for part_phonemes in phonemes:
+            phones, tones = self._get_phone_tone(
+                part_phonemes, get_tone_ids=get_tone_ids)
+            if tones:
+                tone_ids = self._t2id(tones)
+                tone_ids = paddle.to_tensor(tone_ids)
+                temp_tone_ids.append(tone_ids)
+            if phones:
                 phone_ids = self._p2id(phones)
                 phone_ids = paddle.to_tensor(phone_ids)
-        result["phone_ids"] = phone_ids
+                temp_phone_ids.append(phone_ids)
+        if temp_tone_ids:
+            result["tone_ids"] = temp_tone_ids
+        if temp_phone_ids:
+            result["phone_ids"] = temp_phone_ids
         return result

examples/fastspeech2/baker/synthesize_e2e.py

@@ -72,19 +72,25 @@ def evaluate(args, fastspeech2_config, pwg_config):
     std = paddle.to_tensor(std)
     pwg_normalizer = ZScore(mu, std)
 
-    fastspeech2_inferencce = FastSpeech2Inference(fastspeech2_normalizer,
-                                                  model)
+    fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model)
     pwg_inference = PWGInference(pwg_normalizer, vocoder)
 
     output_dir = Path(args.output_dir)
     output_dir.mkdir(parents=True, exist_ok=True)
 
     for utt_id, sentence in sentences:
-        input_ids = frontend.get_input_ids(sentence)
+        input_ids = frontend.get_input_ids(sentence, merge_sentences=True)
         phone_ids = input_ids["phone_ids"]
+        flags = 0
+        for part_phone_ids in phone_ids:
             with paddle.no_grad():
-            mel = fastspeech2_inferencce(phone_ids)
-            wav = pwg_inference(mel)
+                mel = fastspeech2_inference(part_phone_ids)
+                temp_wav = pwg_inference(mel)
+                if flags == 0:
+                    wav = temp_wav
+                    flags = 1
+                else:
+                    wav = paddle.concat([wav, temp_wav])
         sf.write(
             str(output_dir / (utt_id + ".wav")),
             wav.numpy(),

parakeet/frontend/cn_frontend.py

@@ -116,7 +116,9 @@ class Frontend():
                 phones.append('sp')
             phones_list.append(phones)
         if merge_sentences:
-            phones_list = sum(phones_list, [])
+            merge_list = sum(phones_list, [])
+            phones_list = []
+            phones_list.append(merge_list)
         return phones_list
 
     def _merge_erhua(self, initials, finals, word, pos):
@@ -136,7 +138,8 @@ class Frontend():
                 new_initials.append(initials[i])
         return new_initials, new_finals
 
-    def get_phonemes(self, sentence, with_erhua=True):
+    def get_phonemes(self, sentence, merge_sentences=True, with_erhua=True):
         sentences = self.text_normalizer.normalize(sentence)
-        phonemes = self._g2p(sentences, with_erhua=with_erhua)
+        phonemes = self._g2p(
+            sentences, merge_sentences=merge_sentences, with_erhua=with_erhua)
         return phonemes