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Large Vocabulary Mandarin Speech Recognition With Different Approaches in Modeling Tones

机译:大型词汇普通话语音识别,采用造型色调的不同方法

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Large vocabulary continuous Mandarin speech recognition has been an important problem for speech recognition researchers for several reasons [1], [3]. First, of all, it is a tonal language that requires special treatment for the modeling of tones. There are five tones in mandarin which are necessary to disambiguate between confusable words. Secondly, the difficulty of entering Chinese by keyboard presents a great opportunity for speech recognition to improve computer usability. Previous approaches to modeling tones have included using a separate tone classifier [1] and incorporating pitch directly into the feature vector [3]. In this paper, we describe a large vocabulary Mandarin speech recognition system based on Microsoft's Whisper system. Several alternatives in modeling tones and their error rates on continuous speech are compared.
机译:大型词汇持续普通话语音识别是语音识别研究人员的重要问题,因为有几个原因[1],[3]。首先,所有的色调语言需要特殊处理音调的造型。普通话中有五种色调,这是消除混淆词之间的消除歧义。其次,键盘进入中文的难度为语音识别提供了一个很好的机会,以提高计算机可用性。以前的建模音调方法已经包括使用单独的色调分类器[1]并将间距直接结合到特征向量中[3]。在本文中,我们描述了一种基于微软耳语系统的大型词汇普通话语音识别系统。比较了若干建模音调的替代品及其在连续语音上的错误率。

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