Speaker Identification and Verification Using Support Vector Machines and Sparse Kernel Logistic Regression

机译：使用支持向量机和稀疏核逻辑回归的说话人识别和验证

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In this paper we investigate two discriminative classification approaches for frame-based speaker identification and verification, namely Support Vector Machine (SVM) and Sparse Kernel Logistic Regression (SKLR). SVMs have already shown good results in regression and classification in several fields of pattern recognition as well as in continuous speech recognition. While the non-probabilistic output of the SVM has to be translated into conditional probabilities, the SKLR produces the probabilities directly. In speaker identification and verification experiments both discriminative classification methods outperform the standard Gaussian Mixture Model (GMM) system on the POLYCOST database.

机译：在本文中，我们研究了两种基于帧的说话人识别和验证的判别分类方法，即支持向量机（SVM）和稀疏核对数回归（SKLR）。 SVM已在模式识别以及连续语音识别的多个领域的回归和分类中显示出良好的效果。虽然必须将SVM的非概率输出转换为条件概率，但SKLR直接产生概率。在说话人识别和验证实验中，两种区分性分类方法均优于POLYCOST数据库上的标准高斯混合模型（GMM）系统。

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《International Workshop on Intelligent Computing in Pattern Analysis/Synthesis(IWICPAS 2006); 20060826-27; Xi'an(CN)》|2006年|P.176-184|共9页
会议地点 Xian(CN)
作者
Marcel Katz; Sven E. Krueger; Martin Schaffoener; Edin Andelic; Andreas Wendemuth;
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作者单位

IESK, Cognitive Systems University of Magdeburg, Germany;

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原文格式 PDF
正文语种 eng
中图分类信息处理（信息加工）;
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2. Minimum classification error-based weighted support vector machine kernels for speaker verification [J] . Suh Y., Kim H. The Journal of the Acoustical Society of America . 2013,第4期

机译：基于最小分类错误的加权支持向量机内核，用于说话人验证
3. Sparse kernel machines with empirical kernel maps for PLDA speaker verification [J] . Wei Rao, Man-Wai Mak Computer speech and language . 2016,第Jula期

机译：带有经验内核映射的稀疏内核机器，用于PLDA说话者验证
4. Speaker Identification and Verification Using Support Vector Machines and Sparse Kernel Logistic Regression [C] . Marcel Katz, Sven E. Krueger, Martin Schaffoener, International Workshop on Intelligent Computing in Pattern Analysis/Synthesis . 2006

机译：使用支持向量机和稀疏内核Logistic回归的扬声器识别和验证
5. Kernel optimization for support vector machines: Application to speaker verification. [D] . Hatch, Andrew Oliver. 2006

机译：支持向量机的内核优化：应用于说话者验证。
6. Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree Logistic Regression Naïve Bayes Tree Artificial Neural Network and Support Vector Machine Algorithms [O] . Viet-Ha Nhu, Ataollah Shirzadi, Himan Shahabi, 2020

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7. Speaker Identification and Verification using Support Vector Machines and Sparse Kernel Logistic Regression [O] . Marcel Katz, Sven E. Krüger, Martin Schafföner, 2008

机译：基于支持向量机和稀疏核Logistic回归的说话人识别与验证
8. Variability Compensated Support Vector Machines Applied to Speaker Verification. [R] . Karam, Z. N., Campbell, W. M. 2016

机译：用于说话人验证的可变补偿支持向量机。

Speaker Identification and Verification Using Support Vector Machines and Sparse Kernel Logistic Regression

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