Abstract
The success of lumped-parameter analogs of the vocal tract suggests that speech spectra may be optimally approximated by a rational function. As a step in this direction, speech spectra have been approximated by a linear combination of Gram polynomials and have been found to be more efficient than a linear combination of trigonometric functions. The original spectra (100 samples in frequency) and the polynomial and trigonometric approximations have been represented by points in their respective Hilbert spaces, the distance between successive points being a measure of the dissimilarity of successive spectra. Segment boundaries are indicated where the distance between successive spectra exceeds a threshold. The effectiveness in segmentation of connected utterances using these spectral forms will be compared. Results will be presented and implications made for real-time machine recognition of speech. [This research was supported by NASA Fellowships and the Electrical Engineering Department at Northeastern University.]
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.
