GMM and kernel-based speaker recognition with the ISIP toolkit

信号处理 Pub Date : 2004-09-29 DOI:10.1109/MLSP.2004.1422996

T. Imbiriba, A. Klautau, N. Parihar, S. Raghavan, J. Picone

引用次数: 1

Abstract

This paper describes an open source framework for developing speaker recognition systems. Among other features, it supports kernel classifiers, such as the support and relevance vector machines. The paper also presents results for the IME corpus using Gaussian mixture models, which outperforms previously published ones, and discusses strategies for applying discriminative classifiers to speaker recognition

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基于GMM和内核的说话人识别与ISIP工具包

本文描述了一个开发说话人识别系统的开源框架。除其他特性外，它还支持内核分类器，例如支持向量机和相关向量机。本文还介绍了使用高斯混合模型对IME语料库的结果，该结果优于先前发表的结果，并讨论了将判别分类器应用于说话人识别的策略

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

信号处理

自引率

0.00%

发文量

5812

期刊介绍： Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.