Embedded Speech Recognition Based on Multiclass Support Vector Machine

文献类型： 外文期刊

第一作者： Zhao Junfeng

作者： Zhao Junfeng;Zhu Yeping

作者机构：

关键词： Embedded System;Speech Recognition;Support Vector Machine (SVM)

期刊名称：MATERIALS, MECHATRONICS AND AUTOMATION, PTS 1-3 （ 影响因子：0.224； ）

ISSN： 1013-9826

年卷期： 2011 年 467-469 卷

页码：

收录情况： SCI

摘要： This paper introduces the characteristics and requirements of speech recognition technology based on embedded platform. It also describes the basic theory and related properties of Support Vector Machine. The advantages and disadvantages of the Multiclass SVM algorithms are analyzed, providing the algorithms principles for training and recognition of SVM application in the embedded speech recognition system. Finally, we proposed a design strategy based on multiclass SVM decision tree classifier, combined with the features of the embedded speech recognition.

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