support for turning off timestamps
| | |
| | | ibest_writer["score"][key] = str(hyp.score) |
| | | |
| | | if text is not None: |
| | | text_postprocessed = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
| | | item = {'key': key, 'value': text_postprocessed} |
| | | asr_result_list.append(item) |
| | | finish_count += 1 |
| | |
| | | format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s", |
| | | ) |
| | | |
| | | hotword_list_or_file = param_dict['hotword'] |
| | | if param_dict is not None: |
| | | hotword_list_or_file = param_dict.get('hotword') |
| | | else: |
| | | hotword_list_or_file = None |
| | | |
| | | if ngpu >= 1 and torch.cuda.is_available(): |
| | | device = "cuda" |
| | | else: |
| | |
| | | ibest_writer["rtf"][key] = rtf_cur |
| | | |
| | | if text is not None: |
| | | text_postprocessed = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
| | | item = {'key': key, 'value': text_postprocessed} |
| | | asr_result_list.append(item) |
| | | finish_count += 1 |
| | |
| | | ibest_writer["score"][key] = str(hyp.score) |
| | | |
| | | if text is not None: |
| | | text_postprocessed = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
| | | item = {'key': key, 'value': text_postprocessed} |
| | | asr_result_list.append(item) |
| | | finish_count += 1 |
| | |
| | | inference=True, |
| | | ) |
| | | |
| | | if param_dict is not None: |
| | | use_timestamp = param_dict.get('use_timestamp', True) |
| | | else: |
| | | use_timestamp = True |
| | | |
| | | finish_count = 0 |
| | | file_count = 1 |
| | | lfr_factor = 6 |
| | |
| | | text, token, token_int = result[0], result[1], result[2] |
| | | time_stamp = None if len(result) < 4 else result[3] |
| | | |
| | | |
| | | if use_timestamp and time_stamp is not None: |
| | | postprocessed_result = postprocess_utils.sentence_postprocess(token, time_stamp) |
| | | else: |
| | | postprocessed_result = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed = "" |
| | | time_stamp_postprocessed = "" |
| | | text_postprocessed_punc = postprocessed_result |
| | |
| | | text_postprocessed, time_stamp_postprocessed, word_lists = postprocessed_result[0], \ |
| | | postprocessed_result[1], \ |
| | | postprocessed_result[2] |
| | | else: |
| | | text_postprocessed, word_lists = postprocessed_result[0], postprocessed_result[1] |
| | | text_postprocessed_punc = text_postprocessed |
| | | if len(word_lists) > 0 and text2punc is not None: |
| | | text_postprocessed_punc, punc_id_list = text2punc(word_lists, 20) |
| | |
| | | inference=True, |
| | | ) |
| | | |
| | | if param_dict is not None: |
| | | use_timestamp = param_dict.get('use_timestamp', True) |
| | | else: |
| | | use_timestamp = True |
| | | |
| | | finish_count = 0 |
| | | file_count = 1 |
| | | lfr_factor = 6 |
| | |
| | | text, token, token_int = result[0], result[1], result[2] |
| | | time_stamp = None if len(result) < 4 else result[3] |
| | | |
| | | if use_timestamp and time_stamp is not None: |
| | | postprocessed_result = postprocess_utils.sentence_postprocess(token, time_stamp) |
| | | else: |
| | | postprocessed_result = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed = "" |
| | | time_stamp_postprocessed = "" |
| | | text_postprocessed_punc = postprocessed_result |
| | |
| | | text_postprocessed, time_stamp_postprocessed, word_lists = postprocessed_result[0], \ |
| | | postprocessed_result[1], \ |
| | | postprocessed_result[2] |
| | | else: |
| | | text_postprocessed, word_lists = postprocessed_result[0], postprocessed_result[1] |
| | | |
| | | text_postprocessed_punc = text_postprocessed |
| | | if len(word_lists) > 0 and text2punc is not None: |
| | | text_postprocessed_punc, punc_id_list = text2punc(word_lists, 20) |
| | |
| | | ibest_writer["score"][key] = str(hyp.score) |
| | | |
| | | if text is not None: |
| | | text_postprocessed = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
| | | item = {'key': key, 'value': text_postprocessed} |
| | | asr_result_list.append(item) |
| | | finish_count += 1 |
| | |
| | | ibest_writer["score"][key] = str(hyp.score) |
| | | |
| | | if text is not None: |
| | | text_postprocessed = postprocess_utils.sentence_postprocess(token) |
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
| | | item = {'key': key, 'value': text_postprocessed} |
| | | asr_result_list.append(item) |
| | | finish_count += 1 |
| | |
| | | return sentence, ts_lists, real_word_lists |
| | | else: |
| | | word_lists = abbr_dispose(word_lists) |
| | | real_word_lists = [] |
| | | for ch in word_lists: |
| | | if ch != ' ': |
| | | real_word_lists.append(ch) |
| | | sentence = ''.join(word_lists).strip() |
| | | return sentence |
| | | return sentence, real_word_lists |