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Feature extraction and classification techniques for speaker recognition: A review

机译:用于说话人识别的特征提取和分类技术:综述

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摘要

In recent scenario speaker recognition is used in many places for security purpose. Speaker recognition is technique which can verify or identify the person who is speaking. It is different than speech recognition system. In this paper we have discussed the feature extraction techniques like Mel Frequency Cepstral Co-efficient (MFCC), Linear Predictive Coding (LPC) etc. and classification techniques like Gaussian Mixture Model (GMM), Artificial Neural Networks (ANN) etc. that is available for speaker recognition. Also the survey is about how to get better efficiency in terms of speaker recognition rate by simply modifying the existing feature extraction and classification techniques.
机译:在最近的场景中,出于安全目的在许多地方都使用了说话人识别。说话者识别是一种可以验证或识别说话者的技术。它不同于语音识别系统。在本文中,我们讨论了特征提取技术(如梅尔频率倒谱系数(MFCC),线性预测编码(LPC)等)和分类技术(如高斯混合模型(GMM),人工神经网络(ANN)等)。可用于说话人识别。该调查还涉及如何通过简单地修改现有特征提取和分类技术来提高说话人识别率的效率。

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