DSP based improved Speech Recognition system

Swapnil D. Daphal, S. Jagtap
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引用次数: 4

Abstract

Processing of large amount of data is an important aspect of Speech Recognition (SR). However, to formulate speech recognition system in small devices is not simple. This paper suggests Digital Signal Processor (DSP) based speech recognition system with improved performance in terms of recognition accuracies and computational cost. The comprehensive survey of various approaches of feature extraction, like Mel Filter Banks with Mel Frequency Cepstrum Coefficients (MFCC) and Cochlear Filter Banks (CFB) with Zero-crossings is given. Amongst various feature classification techniques, the suitability of the Support Vector Machine (SVM) classifier for the proposed system is significant.
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基于DSP的改进语音识别系统
海量数据的处理是语音识别的一个重要方面。然而,在小型设备上制定语音识别系统并不简单。本文提出了一种基于数字信号处理器(DSP)的语音识别系统,该系统在识别精度和计算成本方面都有所提高。综合介绍了各种特征提取方法,如具有Mel频率倒谱系数的Mel滤波器组(MFCC)和具有零交叉的Cochlear滤波器组(CFB)。在各种特征分类技术中,支持向量机(SVM)分类器对所提出的系统的适用性非常重要。
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