Using different feature vectors, the effect of the vocoders differs on speaker dependent continuous speech recognition and speaker independent connected digits recognition.
对于特定人连续语音识别系统和非特定人连接词识别系统，在使用不同的特征矢量时，不同编码器产生的识别效果有比较大的差异。
Combined with characteristics of Chinese speech language, this paper presents a speaker dependent and independent medium and small vocabulary isolated words recognition system based on TMS320VC5507.
本文结合汉语语音特点，在TMS320VC5507芯片上实现了高性能特定人与非特定人中小词汇量孤立词识别系统。
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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