基于中文语义-音韵信息的语音识别文本校对模型

仲美玉; 吴培良; 窦燕; 刘毅; 孔令富

doi:10.11959/j.issn.1000-436x.2022222

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基于中文语义-音韵信息的语音识别文本校对模型

学术论文 | 更新时间：2024-06-05

- 基于中文语义-音韵信息的语音识别文本校对模型
- Chinese semantic and phonological information-based text proofreading model for speech recognition
- 通信学报 2022年43卷第11期页码：65-79
- 作者机构：
  
  1. 燕山大学信息科学与工程学院，河北秦皇岛 066004
  2. 河北省计算机虚拟技术与系统集成重点实验室，河北秦皇岛 066004
  3. 河北省软件工程重点实验室，河北秦皇岛 066004
- 作者简介：
  
  [ "仲美玉（1993− ），女，河北邢台人，燕山大学博士生，主要研究方向为智能信息处理" ]
  [ "吴培良（1981− ），男，河北石家庄人，博士，燕山大学教授、博士生导师，主要研究方向为自然语言处理、深度强化学习、机器人操作技能学习" ]
  [ "窦燕（1968− ），女，陕西西安人，博士，燕山大学教授、硕士生导师，主要研究方向为智能信息处理、机器视觉与模式识别" ]
  [ "刘毅（1998− ），男，河北石家庄人，燕山大学硕士生，主要研究方向为智能信息处理、机器视觉" ]
  [ "孔令富（1957− ），男，吉林公主岭人，博士，燕山大学教授、博士生导师，主要研究方向为智能控制与智能信息处理、机器人视觉" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2018YFB1308300);国家自然科学基金资助项目(62276028);国家自然科学基金资助项目(U20A20167);北京市自然科学基金资助项目(4202026);河北省自然科学基金资助项目(F202103079);河北省创新能力提升计划基金资助项目(22567626H);河北省创新能力提升计划基金资助项目(22567637H)
- DOI：10.11959/j.issn.1000-436x.2022222
  中图分类号： TP391
- 网络出版日期：2022-11，
  
  纸质出版日期：2022-11-25
- 稿件说明：
移动端阅览
仲美玉, 吴培良, 窦燕, 等. 基于中文语义-音韵信息的语音识别文本校对模型[J]. 通信学报, 2022,43(11):65-79.

Meiyu ZHONG, Peiliang WU, Yan DOU, et al. Chinese semantic and phonological information-based text proofreading model for speech recognition[J]. Journal on communications, 2022, 43(11): 65-79.
仲美玉, 吴培良, 窦燕, 等. 基于中文语义-音韵信息的语音识别文本校对模型[J]. 通信学报, 2022,43(11):65-79. DOI： 10.11959/j.issn.1000-436x.2022222.

Meiyu ZHONG, Peiliang WU, Yan DOU, et al. Chinese semantic and phonological information-based text proofreading model for speech recognition[J]. Journal on communications, 2022, 43(11): 65-79. DOI： 10.11959/j.issn.1000-436x.2022222.

摘要

为了研究拼音对检测和纠正语音识别文本错误的影响，提出了一种基于中文语义-音韵信息的文本校对模型。定义了5种拼音编码方法构建字符-音韵嵌入向量，以此作为基于GRU的Seq2Seq模型的输入，并应用注意力机制提取语句的语义-音韵信息来校对语音识别文本错误。针对标注语料不足的问题，提出了一种基于拼音声韵置换的数据增强方法。在 AISHELL-3 公开数据集的实验结果表明，拼音携带的音韵信息有利于校对语音识别文本错误，所提方法可提升模型的检错性能。

Abstract

To study the influence of Chinese Pinyin on detecting and correcting text errors in speech recognition

a text proofreading model based on Chinese semantic and phonological information was proposed.Five Pinyin coding methods were designed to construct the character-Pinyin embedding vector that was employed as the input of the Seq2Seq model based on gated recurrent unit.At the same time

the attention mechanism was adopted to extract the Chinese semantic and phonological information of sentences to correct speech recognition errors.Aiming at the problem of insufficient labeled corpus

a data augmentation method was introduced

which could automatically obtain annotated corpora by exchanging the initials or finals of Chinese Pinyin.The experimental results on AISHELL-3’s public data show that phonological information is conducive to the text proofreading model to detect and correct text errors after speech recognition

and the proposed data augmentation method can improve the error detection performance of the model.

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Keywords

references

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