Abstract
A speaker-dependent, isolated-word speech recognition system is presented which is based on the use of the fast Fourier transform for extracting features from the speech input. The algorithm then normalizes those features and compares them against previously stored word templates using dynamic time warping in order to identify the uttered word. The system has been successfully implemented and provided good results when tested using a small dictionary.
Sign-in/Register to access full text options 
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.
