Abstract
This paper proposes a new feature extraction method called multi-directional local feature (MDLF) to apply on an automatic speaker recognition system. To obtain MDLF, a linear regression is applied on FFT signal in four different directions which are horizontal (time axis), vertical (frequency axis), diagonal 45 degree (time-frequency) and diagonal 135 degree (time-frequency). In the experiments, Gaussian mixture model with different number of mixtures is used as classifier. Different experiments were conducted using all alphabets of Arabic for speaker recognition systems. Experimental results show that the proposed MDLF achieves better recognition accuracies than the traditional MFCC and Local features for speaker recognition system.
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.
