对多种隐马尔可夫模型算法进行了分析对比,在此基础上设计了一种改进的离散隐马尔可夫模型(DHMM)算法,并将此算法成功运用到了DSP嵌入式语音识别系统中.该系统采用上述算法完成了对非特定人的孤立词语音识别.该系统以ADSP-BF531语音处理专用DSP为核心,并辅以大容量的SDRAM和ROM为扩展,具有小型、高速、可靠、鲁棒性好、扩展性强等多个优点；可应用于许多特定场合,有很好的市场前景.试验结果表明,该系统对非特定人的孤立词的综合识别率在94％以上.对该系统应用的改进的DHM算法,硬件的实现过程以及其实际应用效果等进行了详细阐述.%This paper analysed and contrasted multi-algorithms about DHMM (Discrete Hidden Markov Models), based on which it designed an improved DHMM algorithm, and then, applied it to the embedded speech recognition system. This system was realization of speaker-independent's isolated word recognition. The flatform of this system was centered ADSP-BF531. And it was expanded by big capacity SDRAM & ROM. This system has many merits, e.g. Small volume, high speedand, high reliability, high robustness and high expansibility, etc. It is very convenient for some special situations and has much market potential. The experiment confirms that its speech recognition accuracy reaches 94 percent for speaker-independent and small vocabulary. This paper introduced the improved HMM algorithm, hardware design and its application effect.
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