Merge pull request #1075 from alibaba-damo-academy/dev_lzr_en

fix paraformer-en model python onnx postprocess

runtime/python/onnxruntime/funasr_onnx/paraformer_bin.py

@@ -14,7 +14,8 @@ import numpy as np
 from .utils.utils import (CharTokenizer, Hypothesis, ONNXRuntimeError,
                           OrtInferSession, TokenIDConverter, get_logger,
                           read_yaml)
-from .utils.postprocess_utils import sentence_postprocess
+from .utils.postprocess_utils import (sentence_postprocess,
+                                      sentence_postprocess_sentencepiece)
 from .utils.frontend import WavFrontend
 from .utils.timestamp_utils import time_stamp_lfr6_onnx
 from .utils.utils import pad_list, make_pad_mask
@@ -86,6 +87,10 @@ class Paraformer():
             self.pred_bias = config['model_conf']['predictor_bias']
         else:
             self.pred_bias = 0
+        if "lang" in config:
+            self.language = config['lang']
+        else:
+            self.language = None
 
     def __call__(self, wav_content: Union[str, np.ndarray, List[str]], **kwargs) -> List:
         waveform_list = self.load_data(wav_content, self.frontend.opts.frame_opts.samp_freq)
@@ -111,7 +116,10 @@ class Paraformer():
                 preds = self.decode(am_scores, valid_token_lens)
                 if us_peaks is None:
                     for pred in preds:
-                        pred = sentence_postprocess(pred)
+                        if self.language == "en-bpe":
+                            pred = sentence_postprocess_sentencepiece(pred)
+                        else:
+                            pred = sentence_postprocess(pred)
                         asr_res.append({'preds': pred})
                 else:
                     for pred, us_peaks_ in zip(preds, us_peaks):

runtime/python/onnxruntime/funasr_onnx/utils/postprocess_utils.py

@@ -240,3 +240,54 @@ def sentence_postprocess(words: List[Any], time_stamp: List[List] = None):
                 real_word_lists.append(ch)
         sentence = ''.join(word_lists).strip()
         return sentence, real_word_lists
+
+def sentence_postprocess_sentencepiece(words):
+    middle_lists = []
+    word_lists = []
+    word_item = ''
+
+    # wash words lists
+    for i in words:
+        word = ''
+        if isinstance(i, str):
+            word = i
+        else:
+            word = i.decode('utf-8')
+
+        if word in ['<s>', '</s>', '<unk>', '<OOV>']:
+            continue
+        else:
+            middle_lists.append(word)
+
+    # all alpha characters
+    for i, ch in enumerate(middle_lists):
+        word = ''
+        if '\u2581' in ch and i == 0:
+            word_item = ''
+            word = ch.replace('\u2581', '')
+            word_item += word
+        elif '\u2581' in ch and i != 0:
+            word_lists.append(word_item)
+            word_lists.append(' ')
+            word_item = ''
+            word = ch.replace('\u2581', '')
+            word_item += word
+        else:
+            word_item += ch
+    if word_item is not None:
+        word_lists.append(word_item)
+    #word_lists = abbr_dispose(word_lists)
+    real_word_lists = []
+    for ch in word_lists:
+        if ch != ' ':
+            if ch == "i":
+                ch = ch.replace("i", "I")
+            elif ch == "i'm":
+                ch = ch.replace("i'm", "I'm")
+            elif ch == "i've":
+                ch = ch.replace("i've", "I've")
+            elif ch == "i'll":
+                ch = ch.replace("i'll", "I'll")
+            real_word_lists.append(ch)
+    sentence = ''.join(word_lists)
+    return sentence, real_word_lists