Abstract
Speaker recognition has made great progress under the laboratory environment, but in real life the performance of speaker recognition system is affected by various factors including environmental noise. This paper studies the performance of speaker recognition system in noisy environment and presents Speaker recognition system using modified Mel-Frequency Cepstral Coefficients (MFCC) technique based on different classifiers likes Euclidean distance, Back-Propagation Neural Network (BPNN), Self Organizing Map (SOM). Modified Mel-Frequency Cepstral Coefficients (MFCC) technique includes Blackman windowing instead of hamming window. This paper presents comparative plots of different classifiers based on modified Mel-Frequency Cepstral Coefficients (MFCC) technique. Speaker recognition system based on SOM Neural Network classifier provides better recognition rate compare to BPNN and Euclidean Distance based systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
