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Research on the Key Technologies fo Speech Recognition for Robot Communication

Author: Liu
Tutor: LiuZhiJing;ZuoGuoYong
School: Xi'an University of Electronic Science and Technology
Course: Computer technology
Keywords: Robot Speech recognition Hidden Markov model (HMM)
CLC: TN912.34
Type: Master's thesis
Year: 2009
Downloads: 118
Quote: 0
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The robot development so far , the robot control , voice control is nothing more than the most natural , the most convenient control . From the current situation at home and abroad on the voice recognition technology to communicate with the robot used in robot voice recognition technology is becoming the focus of current research . The voice recognition technology allows the robot to be able to understand the natural language of the person , obtained by the identification information as a voice signal applied to the field of robotics a variety of techniques . Used in robot voice recognition technology has brought great convenience for the user . Therefore research and development of the utility of the robot voice recognition system for the extensive application of the robot having a significance . The main content of the paper are as follows : First, based on the basic principle of speech recognition , research oriented robot dialogue key technologies of speech recognition , the preprocessing of the speech signal , including the sampling, noise removal , endpoint detection , pre-emphasis , adding windows stars frames , etc.; performance of linear predictive cepstral coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC) ; the mainstream model training and pattern matching technology , which is the core part of the speech recognition technology , including hidden Markov Models (HMM), dynamic Time Warping (DTW), vector quantization (VQ) , artificial neural network ( ANN ) , HMM and ANN hybrid model and so on . Secondly, the design of the completion of the voice recognition control system of the robot . VC - based integrated development environment to write the speech recognition software control system , to achieve better recognition performance , higher efficiency of the implementation of the robot voice command recognition algorithm . AS-R robot testing , combined with the use of sonar and PSD sensor , greatly improve robot interaction . The experimental results show that the better the recognition performance of the voice recognition control system implemented . The same time , the system structure is simple , cost-effective, easy - to - function expansion and transplantation , has broad application prospects .

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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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