{"title":"中英文混合关键词识别","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":"{\"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}","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
摘要
基于我们在“工研104自动话务员系统”中使用关键词识别进行普通话语音识别的经验。Shieh et al., CCL technology Journal, vol. 96),提出了一个中英文混合语言关键字识别系统,它迎合了台湾人的说话风格。对混合语言自动服务员系统的开发进行了详细的描述和讨论,特别是解决了两种语言在解码阶段和重新评分阶段的不同评分尺度。在解码阶段,我们提出了一种偏差补偿方法来弥补使用中英文声学模型进行似然计算时的得分差距。为了从识别的假设中选择最可能的结果,还提出了在重新评分阶段使用不同评分机制时对组合分数进行归一化的方法。
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.