外文翻譯機(jī)器人語音識(shí)別算法的研究畢業(yè)論文-資料下載頁
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【正文】 nit of speech (., the sentence) remains less than 90%. Dragon39。s Naturally Speaking or IBM39。s ViaVoice, for example, show a baseline recognition accuracy of only 60% to 80%, depending upon accent, background noise, type of utterance, etc. (Ehsani amp。 Knodt, 1998). More expensive systems that are reported to outperform these two are Subarashii (Bernstein, et al., 1999), EduSpeak (Franco, et al., 2001), Phonepass (Hinks, 2001), ISLE Project (Menzel, et al., 2001) and RAD (CSLU, 2003). ASR accuracy is expected to improve. Among several types of speech recognizers used in ASR products, both implemented and proposed, the Hidden Markov Model (HMM) is one of the most dominant algorithms and has proven to be an effective method of dealing with large units of speech (Ehsani amp。 Knodt, 1998). Detailed descriptions of how the HHM model works go beyond the scope of this paper and can be found in any text concerned with language processing。 among the best are Jurafsky amp。 Martin (2000) and Hosom, Cole, and Fanty (2003). Put simply, HMM putes the probable match between the input it receives and phonemes contained in a database of hundreds of native speaker recordings (Hinks, 2003, p. 5). That is, a speech recognizer based on HMM putes how close the phonemes of a spoken input are to a corresponding model, based on probability theory. High likelihood represents good pronunciation。 low likelihood represents poor pronunciation (Larocca, et al., 1991). While ASR has been monly used for such purposes as business dictation and special needs accessibility, its market presence for language learning has increased dramatically in recent years (Aist, 1999。 Eskenazi, 1999。 Hinks, 2003). Early ASRbased software programs adopted templatebased recognition systems which perform pattern matching using dynamic programming or other time normalization techniques (Dalby amp。 KewleyPort, 1999). These programs include Talk to Me (Auralog, 1995), the Tell Me More Series (Auralog, 2000), TriplePlay Plus (Mackey amp。 Choi, 1998), New Dynamic English (DynEd, 1997), English Discoveries (Edusoft, 1998), and See it, Hear It, SAY IT! (CPI, 1997). Most of these programs do not provide any feedback on pronunciation accuracy beyond simply indicating which written dialogue choice the user has made, based on the closest pattern match. Learners are not told the accuracy of their pronunciation. In particular, Neri, et al. (2002) criticizes the graphical wave forms presented in products such as Talk to Me and Tell Me More because they look flashy to buyers, but do not give meaningful feedback to users. The 2000 version of Talk to Me has incorporated more of the features that Hinks (2003), for example, believes are useful to learners:★ A visual signal allows learners to pare their intonation to that of the model speaker.★ The learners39。 pronunciation accuracy is scored on a scale of seven (the higher the better).Words whose pronunciation fails to be recognized are highligh
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