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Hardware Implementation of MFCC-Based Feature Extraction for Speaker Recognition

机译:基于MFCC的说话人识别特征提取的硬件实现

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The most important issues in the field of speech recognition and representative of the speech is a feature extraction. Feature extraction based Mel Frequency Cepstral Coefficient (MFCC) is one the most important features required among various kinds of speech application. In this paper, FPGA-based for speech features extraction MFCC algorithm is proposed. The complexities of computational as well as the requirement of memory usage are characterized, analyzed, and improved. Look-up table (LUT) scheme is used to deal with the elementary function value in the MFCC algorithm and fixed-point arithmetic is implemented to reduce the cost under accuracy study. The final feature extraction design is implemented effectively into the FPGA-Xilinx Virtex2 XC2V6000 FF1157-4 chip.
机译:语音识别和语音代表领域中最重要的问题是特征提取。基于特征提取的梅尔频率倒谱系数(MFCC)是各种语音应用程序中所需的最重要特征之一。本文提出了一种基于FPGA的语音特征提取MFCC算法。表征,分析和改进了计算的复杂性以及对内存使用的要求。在精度研究中,使用查找表(LUT)方案处理MFCC算法中的基本函数值,并执行定点算法以降低成本。最终功能提取设计已有效地实现到FPGA-Xilinx Virtex2 XC2V6000 FF1157-4芯片中。

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