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infer for word punc model

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shixian.shi 2024-03-06 15:31:47 +08:00
parent 294c1162df
commit e451eb799a
1 changed files with 16 additions and 1 deletions
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funasr/models/ct_transformer/model.py
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@ -3,6 +3,7 @@
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
# MIT License (https://opensource.org/licenses/MIT)
import copy
import torch
import numpy as np
import torch.nn.functional as F
@ -341,11 +342,25 @@ class CTTransformer(torch.nn.Module):
new_mini_sentence_out = new_mini_sentence + "."
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [self.sentence_end_id]
if len(punctuations): punctuations[-1] = 2
# keep a punctuations array for punc segment
# keep a punctuations array for punc segment
if punc_array is None:
punc_array = punctuations
else:
punc_array = torch.cat([punc_array, punctuations], dim=0)
# post processing when using word level punc model
if jieba_usr_dict:
len_tokens = len(tokens)
new_punc_array = copy.copy(punc_array).tolist()
# for i, (token, punc_id) in enumerate(zip(tokens[::-1], punc_array.tolist()[::-1])):
for i, token in enumerate(tokens[::-1]):
if '\u0e00' <= token[0] <= '\u9fa5': # ignore en words
if len(token) > 1:
num_append = len(token) - 1
ind_append = len_tokens - i - 1
for _ in range(num_append):
new_punc_array.insert(ind_append, 1)
punc_array = torch.tensor(new_punc_array)
result_i = {"key": key[0], "text": new_mini_sentence_out, "punc_array": punc_array}
results.append(result_i)
return results, meta_data