太原理工大学学报2011，Vol.42Issue(1)：34-37,4.
基于纠错输出编码的支持向量机在语音识别中的应用
Speech Recognition Based on Support Vector Machine and Error Correcting Output Codes
摘要
Abstract
A method was proposed based on application of Error Correcting Output Codes Support Vector Machine (ECOC-SVM) in order to get better results of speech recognition. Some uncorrelated SVMs were constructed based on ECOC matrix codes to improve the integrated performance of fault tolerance of classification model. This paper gives four commonly used encodings of ECOC: One versus the rest, One versus one, Dense random and Sparse random. By comparing the results with these of speech recognition based on Hidden Markov Model, the experiments indicate that the ECOC method was more suitable for isolated words of a small vocabulary in Korean spoken by non-specific persons, among which the predicting accuracy of one-versus-one was the highest of all.关键词
语音识别/支持向量机/纠错输出编码Key words
Speech Recognition/ Support Vector Machine/Error Correcting Output Code分类
信息技术与安全科学引用本文复制引用
刘晓峰,张雪英..基于纠错输出编码的支持向量机在语音识别中的应用[J].太原理工大学学报,2011,42(1):34-37,4.基金项目
国家自然科学基金(61072087/F010406) （61072087/F010406）
山西省自然科学基金(20100110201) （20100110201）
太原理工大学青年基金(900103-03020669) （900103-03020669）
