Nios Ii多处理器并行实现,Mel频率倒谱系数和MLP架构在Fpga中的应用:语音识别

Khamlich Salah Eddine, Khamlich Fathallah, Issam Atouf, Benrabh Mohamed
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引用次数: 1

摘要

实时语音处理需要使用能够处理音频源产生的大量信息的快速、可重构的电子电路。本文介绍了用于语音识别的多层感知器(MLP)和MFCC算法的硬件实现。这些算法已在硬件上实现,并在基于可重构电路(FPGA)的板载电子卡上进行了测试。我们还对几种MLP架构进行了比较研究,并与有关硅表面、速度和所需计算资源的成本水平的文献进行了比较研究。在对FPGA电路进行修改后,我们创建了NIOSII处理器,以物理实现ann型mlp和MFCC语音识别算法的架构,并实现实时语音识别功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel Implementation of Nios Ii Multiprocessors, Cepstral Coefficients of Mel Frequency and MLP Architecture in Fpga: the Application of Speech Recognition
Speech processing in real time requires the use of fast, reconfigurable electronic circuits capable of handling large amounts of information generated by the audio source. This article presents hardware implementations of a multilayer perceptron (MLP) and the MFCC algorithm for speech recognition. These algorithms have been implemented in hardware and tested in an on-board electronic card based on a reconfigurable circuit (FPGA). We also present a comparative study between several architectures of MLP and with the literature on the level of costs with regard to the surface of silicon, the speed and the computing resources required. Following the FPGA circuit modification, we created NIOSII processors to physically implement the architecture of ANN-type MLPs and MFCC speech recognition algorithms and perform real-time speech recognition functions.
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