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Utterance verification using prosodic information for Mandarin telephone speech keyword spotting

机译:使用韵律信息对普通话语音关键词进行话语验证

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In this paper, the prosodic information, a very special and important feature in Mandarin speech, is used for Mandarin telephone speech utterance verification. A two-stage strategy, with recognition followed by verification, is adopted. For keyword recognition, 59 context-independent subsyllables, i.e., 22 INITIALs and 37 FINALs in Mandarin speech, and one background/silence model, are used as the basic recognition units. For utterance verification, 12 anti-subsyllable HMMs, 175 context-dependent prosodic HMMs, and five anti-prosodic HMMs, are constructed. A keyword verification function combining phonetic-phase and prosodic-phase verification is investigated. Using a test set of 2400 conversational speech utterances from 20 speakers (12 males and 8 females), at 8.5% false rejection, the proposed verification method resulted in 17.8% false alarm rate. Furthermore, this method was able to correctly reject 90.4% of nonkeywords. Comparison with a baseline system without prosodic-phase verification shows that the prosodic information can benefit the verification performance.
机译:本文将韵律信息作为普通话语音的一个非常特殊和重要的特征,用于普通话电话语音发声验证。采用两阶段策略,先确认再确认。对于关键字识别,将59个上下文无关的子音节(即普通话中的22个INITIAL和37个FINAL)以及一个背景/沉默模型用作基本识别单元。为了进行话语验证,构建了12个反音节HMM,175个上下文相关的韵律HMM和5个反韵律HMM。研究了结合语音阶段和韵律阶段验证的关键词验证功能。使用来自20位说话者(12位男性和8位女性)的2400会话语音的测试集,错误拒绝率为8.5%,所提出的验证方法产生了17.8%的错误警报率。此外,此方法能够正确拒绝90.4%的非关键字。与没有韵律阶段验证的基线系统进行比较表明,韵律信息可以使验证性能受益。

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