Automatic Spelling Correction for ASR Corpus in Traditional Chinese Language using Seq2Seq Models

Yu Chieh Chao, Chia Hui Chang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

The goal of Automatic Speech Recognition (ASR) service is to translate spoken language into text. There exist many factors that will degrade the performance of the ASR system, such as environmental noise, human pronunciation, etc. This research focuses on automatic spelling correction for traditional Chinese corpus generated by ASR systems. We show that a Sequence to Sequence (Seq2Seq) neural network model with attention mechanism could be improved by adding pointer network with auxiliary phoneme features of the input word sequence.

原文???core.languages.en_GB???
主出版物標題Proceedings - 2020 International Computer Symposium, ICS 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面553-558
頁數6
ISBN(電子)9781728192550
DOIs
出版狀態已出版 - 12月 2020
事件2020 International Computer Symposium, ICS 2020 - Tainan, Taiwan
持續時間: 17 12月 202019 12月 2020

出版系列

名字Proceedings - 2020 International Computer Symposium, ICS 2020

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???2020 International Computer Symposium, ICS 2020
國家/地區Taiwan
城市Tainan
期間17/12/2019/12/20

指紋

深入研究「Automatic Spelling Correction for ASR Corpus in Traditional Chinese Language using Seq2Seq Models」主題。共同形成了獨特的指紋。

引用此