在孤立词语音识别中，最为简单有效的方法是采用DTW（Dynamic Time Warping，动态时间归整）算法，该算法基于动态规划（DP）的思想，解决了发音长短不一的模板匹配问题，是语音识别中出现较早、较为经典的一种算法，用于孤立词识别。HMM算法在训练阶段需要提供大量的语音数据，通过反复计算才能得到模型参数，而DTW算法的训练中几乎不需要额外的计算。所以在孤立词语音识别中，DTW算法仍然得到广泛的应用。-In isolated word speech recognition, the most simple and effective method is to use DTW (Dynamic Time Warping, Dynamic Time whole) algorithm based on dynamic programming (DP) of thinking to solve the problem of template matching pronunciation of varying lengths, is Earlier, more classic appearance of a speech recognition algorithm for isolated word recognition. In the training phase HMM algorithm needs to provide a large amount of speech data, by repeating the calculations to obtain the model parameters, and the algorithm of DTW training requires little extra computation. Therefore, in isolated word speech recognition, DTW algorithm is still widely used.