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DSP based improved Speech Recognition system

机译:基于DSP的改进语音识别系统

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摘要

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.
机译:处理大量数据是语音识别(SR)的重要方面。然而,在小型设备中建立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,该系统在识别准确度和计算成本方面具有改进的性能。本文对各种特征提取方法进行了全面的调查,例如具有梅尔频率倒谱系数的梅尔滤波器组(MFCC)和具有零交叉的耳蜗滤波器组(CFB)。在各种特征分类技术中,支持向量机(SVM)分类器对拟议系统的适用性很重要。

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