{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T06:19:46Z","timestamp":1663395586014},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,14]]},"abstract":"<jats:p>Text restoration plays a vital role in Chinese automatic speech recognition (ASR), which includes punctuation prediction and error correction. However, there are two inevitable challenges for this task. On the one hand, there are no public dataset and model for Chinese punctuation prediction. On the other hand, current text restoration methods for automatic speech recognition only focus on Chinese error correction instead of combining with Chinese punctuation prediction task. To address these problems, a BERT-based text restoration method called TRCA is proposed for Chinese ASR consisting of a Chinese punctuation prediction model and a Chinese error correction model. Experiments demonstrate that the proposed TRCA method outperforms state-of-the-art methods for both punctuation prediction and error correction tasks, among which the proposed TRCA improves the average accuracy to 98% in Chinese punctuation prediction.<\/jats:p>","DOI":"10.3233\/faia220295","type":"book-chapter","created":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T09:08:30Z","timestamp":1663319310000},"source":"Crossref","is-referenced-by-count":0,"title":["TRCA: Text Restoration for Chinese ASR with BERT"],"prefix":"10.3233","author":[{"given":"Xing","family":"Wu","sequence":"first","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 20444, China"},{"name":"Shanghai Institute for Advanced Communication and Data Science, Shanghai 20444, China"}]},{"given":"Yuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 20444, China"}]},{"given":"Jianjia","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 20444, China"},{"name":"Shanghai Institute for Advanced Communication and Data Science, Shanghai 20444, China"}]},{"given":"Yike","family":"Guo","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong, 999077, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220295","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T09:08:30Z","timestamp":1663319310000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220295"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,14]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220295","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,14]]}}}