| 对MFCC进行GMM聚类的汉语数字识别方法 |
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| 引用本文： | 高文曦,于凤芹.对MFCC进行GMM聚类的汉语数字识别方法[J].计算机系统应用,2011,20(11):167-170. |
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| 作者姓名： | 高文曦 于凤芹 |
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| 作者单位： | 江南大学物联网工程学院,无锡,214122 |
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| 摘 要： | 汉语数字识别常用MFCC作为特征,针对0-9十个数字MFCC样本特征数据量大的问题,提出了用GMM模型对提取的特征参数MFCC的数据进行聚类来减少数据量,以GMM模型参数中的均值作为新的特征,采用动态规划算法进行汉语数字语音识别.仿真实验表明,进行GMM特征变换后的新特征数据为MFCC的30.9％,系统运行时间减少了2...
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| 关 键 词： | 汉语数字识别 MFCC GMM聚类 |
| 收稿时间： | 2011/3/15 0:00:00 |
| 修稿时间： | 2011/4/13 0:00:00 |
Chinese Digital Identification Based on MFCC by Using GMM Clustering |
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| GAO Wen-Xi and YU Feng-Qin.Chinese Digital Identification Based on MFCC by Using GMM Clustering[J].Computer Systems& Applications,2011,20(11):167-170. |
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| Authors: | GAO Wen-Xi and YU Feng-Qin |
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| Affiliation: | GAO Wen-Xi,YU Feng-Qin(School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China) |
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| Abstract: | MFCC is widely used in Chinese digital identification.Because the amount of MFCC extracted from 0-9 is too large,the mean of model parameters which is clustered with GMM by MFCC to reduce the amount is employed as a new feature with DTW for Chinese digital identification.Simulation results demonstrate that the amount of the new feature is 30.9% to that of MFCC,the running time reduces by 237.18s,but the recognition rate decreases by 1.11%. |
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| Keywords: | Chinese digital identification MFCC GMM clustering |
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