Automatic Isolated Speech Recognition System Using MFCC Analysis - Faisal, Mohammad;Ullah, Aasim;Shakil, Daud
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This is all about a successfully implemented research project which is expected to be a commercial product in future. Objective of the research is to develop an Automatic Isolated Speech Recognition System (AISR) which will be able to classify four distinct words class enunciated as "GO", "STOP", "LEFT" and "RIGHT". Speech data are analyzed mainly with Mel Frequency Cepstrum Coefficients (MFCC) analysis along with some subsidiary DSP processing to create compact and prolific speech database. While Artificial Neural Network (ANN) is used as a classifier or recognizer to classify among the four…mehr

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Produktbeschreibung
This is all about a successfully implemented research project which is expected to be a commercial product in future. Objective of the research is to develop an Automatic Isolated Speech Recognition System (AISR) which will be able to classify four distinct words class enunciated as "GO", "STOP", "LEFT" and "RIGHT". Speech data are analyzed mainly with Mel Frequency Cepstrum Coefficients (MFCC) analysis along with some subsidiary DSP processing to create compact and prolific speech database. While Artificial Neural Network (ANN) is used as a classifier or recognizer to classify among the four distinct word classes. In order to justify feasibility and effectiveness of proposed ASR system a small scale application is implemented as well with designated speech classes.
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Autorenporträt
Dr. Mohammad Faisal is an Assistant Professor at the Department of Botany & Microbiology, King Saud University, Saudi Arabia. Dr. Faisal earned his Ph.D. degree in Botany from the Aligarh Muslim University, India in the year 2006. He has done Postdoctoral Research with Dr. Pilar S. Testillano at the Biological Research Centre (CIB), Madrid, Spain