{"title":"Chinese-English mixed-lingual keyword spotting","authors":"Shan-Ruei You, Shih-Chieh Chien, Chih-Hsing Hsu, Ke-Shiu Chen, Jia-Jang Tu, Jeng-Shien Lin, Sen-Chia Chang","doi":"10.1109/CHINSL.2004.1409630","DOIUrl":null,"url":null,"abstract":"Base on our former experience in the \"ITRI 104 Auto Attendant System\" of using keyword spotting for Mandarin speech recognition (W.-C. Shieh et al., CCL Technical Journal, vol. 96), a Chinese-English mixed-lingual keyword spotting system, which caters for the Taiwanese speaking style, is presented. Detailed descriptions and discussions for developing the mixed-lingual auto attendant system are included, especially for solving different scoring scales in the decoding phase and the re-scoring phase for the two languages. In the decoding phase, we propose a bias-compensation method to make up the score-gap in the likelihood calculation of using Chinese and English acoustic models. To select the most probable result from the recognized hypotheses, a method is also presented of normalizing the combination scores when using different scoring mechanisms in the re-scoring phase.","PeriodicalId":212562,"journal":{"name":"2004 International Symposium on Chinese Spoken Language Processing","volume":"8 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Symposium on Chinese Spoken Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CHINSL.2004.1409630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Base on our former experience in the "ITRI 104 Auto Attendant System" of using keyword spotting for Mandarin speech recognition (W.-C. Shieh et al., CCL Technical Journal, vol. 96), a Chinese-English mixed-lingual keyword spotting system, which caters for the Taiwanese speaking style, is presented. Detailed descriptions and discussions for developing the mixed-lingual auto attendant system are included, especially for solving different scoring scales in the decoding phase and the re-scoring phase for the two languages. In the decoding phase, we propose a bias-compensation method to make up the score-gap in the likelihood calculation of using Chinese and English acoustic models. To select the most probable result from the recognized hypotheses, a method is also presented of normalizing the combination scores when using different scoring mechanisms in the re-scoring phase.