Abstract
The aim of this study is to evaluate how far the nonlinear symbolic dynamics approach helps to characterize the nonlinear properties of speech and thereby discriminate between voiced and unvoiced speech segments. The symbolic dynamics calculations were performed on voiced speech, unvoiced speech and silence data. Differences were found in histogram properties and complexity measures of symbol sequences among the three groups. The results of the analysis suggest that the nonlinear symbolic dynamics approach is helpful in classification of speech segments.
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.
