For speaker identification, Expectation Maximization Algorithm (EM) is adopted to train speaker dependent model, and afterwards recognize speaker according to Maximum a Posteriori Criterion (MAP).
对于语者辨识，语者特定模型直接用语者的语料借助于期望值最大化算法（EM）来训练，辨识算法采用了最大事后概率法则（MAP）；
A discrete hidden Markov model based on the multiple vector quantization codebooks is used here for speaker-dependent discrete speech recognition in Noisy Environments.
本文介绍多码本离散隐马尔可夫模型用于含噪声语音识别的研究成果。
A discrete hidden Markov model based on the multiple vector quantization codebooks is used here for speaker-dependent discrete speech recognition in Noisy Environments.
本文介绍多码本离散隐马尔可夫模型用于含噪声语音识别的研究成果。
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