| 融合LPC与MFCC的特征参数 |
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| 引用本文： | 张学锋,王芳,夏萍.融合LPC与MFCC的特征参数[J].计算机工程,2011,37(4):216-217. |
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| 作者姓名： | 张学锋 王芳 夏萍 |
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| 作者单位： | 1. 安徽工业大学计算机学院,安徽,马鞍山,243002
2. 中北大学机械工程与自动化学院,太原,030051 |
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| 基金项目： | 安徽省教育厅青年教师基金资助项目，安徽省教育厅基金资助一般项目 |
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| 摘 要： | 在线性预测系数(LPC)的基础上，借鉴美尔倒谱系数(MFCC)计算方法，对LPC进行美尔倒谱计算，得到一种新的特征参数：线性预测美尔倒谱系数(LPMFCC)。在Matlab7.0平台上实现一个基于隐马尔可夫模型(HMM)的说话人识别系统，分别用LPMFCC及其一阶差分、MFCC及其一阶差分和基于小波包分析的特征参数(WPDC)及其一阶差分作为识别参数进行对比实验。结果表明，以LPMFCC作为特征参数的系统具有较高的识别率。
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| 关 键 词： | 线性预测 美尔倒谱系数 说话人识别 |
Feature Factor Fused on LPC and MFCC |
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| ZHANG Xue-feng,WANG Fang,XIA Ping.Feature Factor Fused on LPC and MFCC[J].Computer Engineering,2011,37(4):216-217. |
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| Authors: | ZHANG Xue-feng WANG Fang XIA Ping |
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| Affiliation: | 1.School of Computer Science,Anhui University of Technology,Maanshan 243002,China;2.School of Mechanical Engineering and Automatic,North University of China,Taiyuan 030051,China) |
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| Abstract: | This paper obtains a new feature factor which is called linear prediction Mel Frequency Cepstral Coefficient（MFCC） based on the Linear Prediction Coefficient（LPC） and MFCC. In order to verify the validity of the LPMFCC, a speaker recognition system based on the HMM model using the MatlabT.0 is established. The speech recognition rate of LPMFCC and the other two feature factors are tested. The result suggests that the new feature factor is not only efficiency, but also better than other two feature factors. It can achieve high recognition rate. |
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| Keywords: | linear prediction Mel Frequency Cepstral Coefficient（MFCC） speaker recognition |
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