论文标题
通过考虑语言转移的效果，代表普通话的外语单词的发音建模
Pronunciation Modeling of Foreign Words for Mandarin ASR by Considering the Effect of Language Transfer
论文作者
论文摘要
自动语音识别的挑战之一是外语识别。据观察，说话者对外语的发音受他的母语知识的影响，这种现象被称为语言转移的效果。本文着重研究自动语音识别中语言传递的语音效应。提出了一组词汇规则将英语单词转换为普通话语音表示。这样，可以通过包括英语单词来增强普通话词典。因此，普通话ASR系统能够识别英语单词，而无需重新估算或重新估计声学模型参数。使用源自提议的规则的词典，普通话的ASR表现得到改善，而不会损害仅限普通话的准确性。提出的词汇规则是普遍的，可以直接应用于看不见的英语单词。
One of the challenges in automatic speech recognition is foreign words recognition. It is observed that a speaker's pronunciation of a foreign word is influenced by his native language knowledge, and such phenomenon is known as the effect of language transfer. This paper focuses on examining the phonetic effect of language transfer in automatic speech recognition. A set of lexical rules is proposed to convert an English word into Mandarin phonetic representation. In this way, a Mandarin lexicon can be augmented by including English words. Hence, the Mandarin ASR system becomes capable to recognize English words without retraining or re-estimation of the acoustic model parameters. Using the lexicon that derived from the proposed rules, the ASR performance of Mandarin English mixed speech is improved without harming the accuracy of Mandarin only speech. The proposed lexical rules are generalized and they can be directly applied to unseen English words.
