In order to solve these problems, we proposed a single feature vector recognition model based on whole time-frequency information structure of digit speech.
为了解决这些问题，我们提出了基于数字语音时频信息整体结构的单特征向量识别模型。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
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