• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2024, Vol. 46 ›› Issue (06): 1121-1127.

• Artificial Intelligence and Data Mining • Previous Articles     Next Articles

Text error correction of Burmese speech recognition based on phoneme fusion

CHEN Lu1,2,DONG Ling1,2,WANG Wen-jun1,2,WANG Jian1,2,YU Zheng-tao1,2,GAO Sheng-xiang1,2   

  1. (1.Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500;
    2.Key Laboratory of Artificial Intelligence in Yunnan Province,
    Kunming University of Science and Technology,Kunming 650500,China)
  • Received:2023-09-04 Revised:2023-10-30 Accepted:2024-06-25 Online:2024-06-25 Published:2024-06-19

Abstract: The Burmese language speech recognition text contains a large number of homophones and space errors. General methods use text semantic information to correct erroneous characters, but they are not accurate in locating and correcting Burmese space and homophone errors. Considering that Burmese is a tonal language with tone information embedded within its phonemes, this paper proposes a method for correcting errors in Burmese language speech recognition text that incorporates phonemes. Parameter sharing strategy is used to jointly model the transcribed texts and theirs phonemes, phoneme information is used to assist in detecting and correcting Burmese homophones and space errors. Experimental results show that compared with ConvSeq2Seq method, the F1 value of the proposed method in the Burmese speech recognition correction task has increased by 85.97%, reaching 79.15%.

Key words: Burmese language, speech recognition text correction, phoneme, shared parameter, bidirectional encoder representations from transformers(BERT)