Abstract
An approach to automatic language identification (LID) using pitch contour information is proposed. A segment of pitch contour is approximated by a set of Legendre polynomials so that coefficients of the polynomials form a feature vector to represent this pitch contour. A Gaussian mixture model (GMM) method based on feature vectors extracted from pitch contours is suggested for the LID. Our experiments show that only two or three coefficients are necessary to obtain reasonably good identification rates. We also find that the length of the segmented pitch contour is another useful feature for LID, so that it is included to improve the performance further. Pair-wise language identification experiments on the OGI-TS corpus show that our proposed approach is very promising We also find that tonal languages and pitch accent languages achieve better performance in our system.
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.
