{"title":"声学置信度与语言特征相结合的OOV词检测","authors":"F. Stouten, D. Fohr, I. Illina","doi":"10.1109/ASRU.2009.5372877","DOIUrl":null,"url":null,"abstract":"This paper describes the design of an Out-Of-Vocabulary words (OOV) detector. Such a system is assumed to detect segments that correspond to OOV words (words that are not included in the lexicon) in the output of a LVCSR system. The OOV detector uses acoustic confidence measures that are derived from several systems: a word recognizer constrained by a lexicon, a phone recognizer constrained by a grammar and a phone recognizer without constraints. On top of that it also uses some linguistic features. The experimental results on a French broadcast news transcription task showed that for our approach precision equals recall at 35%.","PeriodicalId":292194,"journal":{"name":"2009 IEEE Workshop on Automatic Speech Recognition & Understanding","volume":"114 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Detection of OOV words by combining acoustic confidence measures with linguistic features\",\"authors\":\"F. Stouten, D. Fohr, I. Illina\",\"doi\":\"10.1109/ASRU.2009.5372877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the design of an Out-Of-Vocabulary words (OOV) detector. Such a system is assumed to detect segments that correspond to OOV words (words that are not included in the lexicon) in the output of a LVCSR system. The OOV detector uses acoustic confidence measures that are derived from several systems: a word recognizer constrained by a lexicon, a phone recognizer constrained by a grammar and a phone recognizer without constraints. On top of that it also uses some linguistic features. The experimental results on a French broadcast news transcription task showed that for our approach precision equals recall at 35%.\",\"PeriodicalId\":292194,\"journal\":{\"name\":\"2009 IEEE Workshop on Automatic Speech Recognition & Understanding\",\"volume\":\"114 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Workshop on Automatic Speech Recognition & Understanding\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASRU.2009.5372877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Workshop on Automatic Speech Recognition & Understanding","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASRU.2009.5372877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of OOV words by combining acoustic confidence measures with linguistic features
This paper describes the design of an Out-Of-Vocabulary words (OOV) detector. Such a system is assumed to detect segments that correspond to OOV words (words that are not included in the lexicon) in the output of a LVCSR system. The OOV detector uses acoustic confidence measures that are derived from several systems: a word recognizer constrained by a lexicon, a phone recognizer constrained by a grammar and a phone recognizer without constraints. On top of that it also uses some linguistic features. The experimental results on a French broadcast news transcription task showed that for our approach precision equals recall at 35%.