Chinese semantic and phonological information-based text proofreading model for speech recognition - Meiyu ZHONG; Peiliang WU; Yan DOU; Yi LIU; Lingfu KONG (Tongxin xuebao)
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.