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MFCC -based speech recognition system to improve research and design

Author: WenLin
Tutor: XiongHongYun
School: Central South University
Course: Control Theory and Control Engineering
Keywords: Speech Recognition Endpoint Detection Pitch Detection Feature Extraction
CLC: TN912.34
Type: Master's thesis
Year: 2011
Downloads: 238
Quote: 4
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As information science and embedded technology continues to evolve , speech recognition technology research and on a new level. Using modern means of voice recognition technology, can effectively help us to produce , store and retrieve voice signals , which promote the development of far-reaching social . This paper presents a frequency standard based on improved Mel cepstrum (MFCC) algorithm for speech recognition and its embedded hardware design . This paper describes the speech recognition algorithms and implemented . At the beginning of the specific voice recognition before the paper first introduces a number of short-time speech recognition functions, including short-time average energy , short-time average zero-crossing rate , short-term autocorrelation function and short average magnitude difference function . These functions for subsequent speech recognition algorithm to pave the way . Endpoint detection for speech recognition difficult problem , consider the DC component of the speech signal interference and misjudgment tail tone , putting forward an improved two-door method . Voice Recognition for pitch detection problem , this paper proposes an improved loop short average magnitude difference function (AMDF) method . To get the best voice characteristic parameters , the paper on the basis of the conventional MFCC , which improves the high band frequency characteristics , an improved method MFCC . Experimental results show that the improved feature extraction method improves the speech recognition rate. In speech recognition model , the paper introduces the dynamic time warping model (DTW), hidden Markov model (HMM) and artificial neural network model (ANN). Using a DTW model identification , the model algorithm is simple, high recognition rate. In this paper, the hardware design for a detailed description . To a Samsung S3C2440 processor as the core , the processor has a powerful hardware resources. This paper presents a processor and SDRAM, FLASH, serial port , JTAG, power supply, external AD, LCD screen, voiced connection circuit modules . This specific identification algorithm in MATLAB simulation, simulation achieved good results. The results illustrate that these algorithms can be widely used in the field of speech recognition , which is the development of speech recognition technology has a certain role in promoting.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Electro-acoustic technology and speech signal processing > Speech Signal Processing > Speech Recognition and equipment
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