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Automatic modeling for adding new words to a large-vocabulary continuous speech recognition system

机译:用于将新单词添加到大型词汇连续语音识别系统的自动建模

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The authors report on the detection of new words for the speaker-dependent and speaker-independent paradigms. A useful operating point in a speaker-dependent paradigm is defined at 71% detection rate and 1% false alarm rate. The authors present a novel technique for obtaining a phonetic transcription for a new word, which is needed to add the new word to the system. The technique utilizes DECtalk's text-to-sound rules to obtain an initial phonetic transcription for the new word. Since these text-to-sound rules are imperfect, a probabilistic transformation technique is used that produces a phonetic pronunciation network of all possible pronunciations given DECtalk's transcription. The network is used to constrain a phonetic recognition process that results in an improved phonetic transcription for the new word. The resulting transcriptions are sufficient for speech recognition purposes.
机译:作者报告了针对依赖说话者和不依赖说话者的范例的新单词的检测。取决于说话者的范例中的一个有用的工作点定义为71%的检测率和1%的虚警率。作者提出了一种用于获取新单词的语音转录的新颖技术,这是将新单词添加到系统中所必需的。该技术利用DECtalk的文本到声音规则来获取新单词的初始语音转录。由于这些文本到声音的规则是不完善的,因此使用了一种概率转换技术,该技术会在给定DECtalk的转录后生成所有可能发音的语音发音网络。该网络用于限制语音识别过程,从而导致新单词的语音转录得到改善。所得的转录足以用于语音识别目的。

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