The audio signal feature, in this scheme, is the LPC Mel Cepstrum Coefficient (LPCMCC) and recognition algorithm is Dynamic Time Warping (DTW).

系统提取的音频信号特征为线性预测美尔倒谱系数（LPCMCC），采用动态时间规整（DTW）的识别算法。

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For the length of feature vectors of speech samples is different, direct cutting and Dynamic Time Warping (DTW) regulation, are put forward to solve the problem.

提出了直接截取和DT W规正两种方法来解决语音样本特征向量长度不一致的问题。

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The paper proposes an online handwriting signature verification algorithm with signature energy as feature based on dynamic time warping (DTW).

提出了一种基于DTW匹配的以签名能量为特征的在线手写签名验证算法。

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