【精品】《心经》图解.ppt

藏语音识别论文:基于快速沃尔什变换的藏语音识别技术
【中文摘要】藏语音识别技术由于研究的起步较晚现在还处于初级阶段,且使用人口众多,能促进藏族同胞与外界的学习交流,影响到民族团结和国家稳定,所以对藏语音识别技术的深入研究和识别系统的广泛应用具有重要意义。对于藏语音孤立词识别而言,当语音库逐渐扩充的时候,识别速度将越来越不能满足实时性的要求,对孤立词识别系统的实际应用造成很大限制。为了解决这个问题,特征参数中,使提取和计算特征参数的时间大为缩短,有利于识别系统实时性的实现。对于连续藏语音识别而言,如何准确的将其分割成可供识别用的藏语音单元是进行连续藏语音识别的重要前提。_FWT的分割算法应用到连续藏语音的分割中,将连续藏语音分割成孤立的语音单元后再进行识别。主要工作和贡献如下:,介绍了藏语音识别系统的基本原理,对预处理和端点检测技术进行深入研究。,并根据其在实际使用中计算速度不尽人意的问题将快速沃尔什变换应用其中,的速度得到很大提升,并且能保证提取参数的有效性。。DTW算法对特定人的孤立词识别简单有效,HMM算法具有极强的建模能力,可以方便的表征任何语音基元,对孤立和连续的藏语音都具有很好的识别效果。,将连续藏语音分割成孤立的藏语音单元后再进行识别,大大简化了连续藏语音识别系统实现的难度。
【英文摘要】The research of Tibetan speech recognition is still in the initial stage due to the various reasons. Because there is a large population use Tibetan and development of the technology can promote academic exchange and connection between Tibet and outside world what makes great sense in promoting national unity and stability. So it plays extremely important role in wide range applications of speech identification speed is one of the most prime targets for the recognition of isolated Tibetan speech. But it will be unable to meet the real-time requirement when the vocabulary increases greatly. The fast Walsh transform was applied to extract the feature parameters instead of to solve this problem. It shortens the duration of parameters calculation and the systems improved the recognition of continuous Tibetan speech, the precision of dividing the continuous speech into units determines the recognition effect. _FWT and screened twice based on Wavelet Transform segmentation algorithm were applied to process the continuous speech of Tibetan. So the continuous speech was divided into units and it could be main work and contributions are as follows:1. Analysis the Tibetan pronunciation features and sentences
’syntactic features firstly. Introduce the basic principles of