基于加权MFCC的音频检索  

Audio retrieval based on weighted MFCC

作　　者：华斌[1] 张丽超[1] 赵富强[1] 

机构地区：[1]天津财经大学信息科学与技术系,天津300222

出　　处：《计算机工程与应用》2015年第8期200-204,共5页Computer Engineering and Applications

基　　金：天津市高等学校科技发展基金计划项目(No.20140816)

摘　　要：通过研究音频特征值提取和特征匹配算法,给出了一个完整的音频数据检索系统框架。该系统框架主要分析了音频特征提取和特征匹配。在音频特征提取部分对经典的MFCC系数进行了分析,提出了基于熵值法加权的MFCC系数,提高了检索的识别率。音频匹配部分根据特征参数矩阵表征音频信息的性质,引入了矩阵相似度的匹配方法,提高了检索效率。实验结果表明系统识别效率提高1.2%,用时降低22%,系统的性能得到明显改善。Through analyzing the feature extraction and the matching algorithm, it proposes a completed framework of audio data retrieval system. The system mainly analyzes the feature extraction and the matching of feature. In the part of audio feature extraction, it analyzes the classical MFCC coefficient and proposes a weighted MFCC coefficient based on the entropy value method, which improves the recognition rate of retrieval. In the part of audio matching, it uses the character-istic parameter matrix to represent the property of audio information, and introduces a matching method of matrix similarity, which improves the retrieval efficienty. The experimental results show that the recognition rate of system increases 1.2%and the time decreases 22%, and the performance of system is improved obviously.

关 键 词：特征提取 音频检索 熵值法 矩阵相似度 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]