Title

语音识别中的一种说话人聚类算法

Translated Titles

Speaker Clustering Algorithm in Speech Recognition

Authors

肖述才(Shu-Cai Xiao);欧智坚(Zhi-Jian Ou);王作英(Zuo-Ying Wang)

Key Words

计算机应用 ; 中文信息处理 ; 说话人聚类 ; 说话人自适应 ; 语音识别 ; computer application ; Chinese information processing ; speaker clustering ; speaker adaptation ; speech recognition

PublicationName

中文信息學報

Volume or Term/Year and Month of Publication

19卷4期(2005 / 07 / 01)

Page #

84 - 88

Content Language

簡體中文

Chinese Abstract

本文介绍了稳健语音识别中的一种说话人聚类算法,包括它在语音识别中的作用和具体的用法,聚类中常用的特征、距离测度,聚类的具体实现步骤等。我们从两个方面对该算法的性能进行了刚试,一是直接计算句子聚类的正确率,二是对说话人自适应效果的改进的作用,即比较使用此算法后系统性能的改进进行评价。实验表明:在使用GLR距离作为距离测度的时候,该算法对句子的聚类正确率达85.69%;在识别实验中,该聚类算法的使用,使得用于说话人自适应的数据更加充分,提高了自适应的效果,系统的误识率已经接近利用已知说话人信息进行自适应时的误识率。

English Abstract

In this paper, We introduced a speaker clustering algorithm in speech recognition, which includes its effect to the recognition system. Also, its usage, the features used, distance measurement and the procedure of the algorithm were de scribed. To evaluate the effectiveness of the algorithm, we do two kinds of experiments. One is by calculating the clustering correction rate directly and the other is by comparing the word error rate (WER) of the recognition system under two different conditions: whether using the speaker clustering algorithm or not. From the experiments, we can see that the sentence clustering correction rate is reached 85.69% when using the GLR distance measurement. In the recognition experiment, the performance of the system improves a lot, that the word error rate is very near that of the system by using the known speaker information to do the speaker adaptation.

Topic Category 基礎與應用科學 > 資訊科學