shixian.shi
2023-03-09 3ff9f5bf779f79750807d706c08b5b5c5943fca0
funasr/bin/tp_inference.py
@@ -91,7 +91,7 @@
    for char, timestamp in zip(new_char_list, timestamp_list):
        res_str += "{} {} {};".format(char, str(timestamp[0]+0.0005)[:5], str(timestamp[1]+0.0005)[:5])
    res = []
    for char, timestamp in zip(char_list, timestamp_list):
    for char, timestamp in zip(new_char_list, timestamp_list):
        if char != '<sil>':
            res.append([int(timestamp[0] * 1000), int(timestamp[1] * 1000)])
    return res_str, res
@@ -114,7 +114,7 @@
        )
        if 'cuda' in device:
            tp_model = tp_model.cuda()
        frontend = None
        if tp_train_args.frontend is not None:
            frontend = WavFrontend(cmvn_file=timestamp_cmvn_file, **tp_train_args.frontend_conf)
@@ -304,7 +304,9 @@
                token = speechtext2timestamp.converter.ids2tokens(batch['text'][batch_id])
                ts_str, ts_list = time_stamp_lfr6_advance(us_alphas[batch_id], us_cif_peak[batch_id], token)
                logging.warning(ts_str)
                tp_result_list.append({'text':"".join([i for i in token if i != '<sil>']), 'timestamp': ts_list})
                item = {'key': key, 'value': ts_str, 'timestamp':ts_list}
                # tp_result_list.append({'text':"".join([i for i in token if i != '<sil>']), 'timestamp': ts_list})
                tp_result_list.append(item)
        return tp_result_list
    return _forward