期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2013
卷号：2
期号：10
页码：2903-2910
出版社：IJECS
摘要：In any language, Spoken alphabet recognition as one of the subsets of speech recognition and pattern recognition has manyapplications. The purpose of audio signal processing, they are classified. Speech recognition is one of the issues in computerscience and artificial intelligence, which seeks to identify a person based on the person's voice. Alphabet Recognition Speechrecognition is below the branches. The different methods of feature extraction and classification, in this paper, a methodcombining these algorithms are trying to improve the English alphabet recognition. We are also leading to problems such as theseproblems can be noted that E-set, this collection contains the letters B, C, D, E, G, P, T, V and Z. The problem is similar to the setof waves vocal alphabet E that makes it difficult to recognize in all this is set in this paper by using MFCC feature extraction andSVM classification methods to achieve our desired results. In this paper, a method is said to have achieved 80% accuracy ondata-set TI ALPHA
关键词：Mel-frequency cepstral coefficients; (MFCC); Support Vector Machines (SVMs).
