Hilbert spectral analysis of vowels using intrinsic mode functions

Steven Sandoval, Phillip L. De Leon, Julie Liss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In recent work, we presented mathematical theory and algorithms for time-frequency analysis of non-stationary signals. In that work, we generalized the definition of the Hilbert spectrum by using a superposition of complex AM-FM components parameterized by the Instantaneous Amplitude (IA) and Instantaneous Frequency (IF). Using our Hilbert Spectral Analysis (HSA) approach, the IA and IF estimates can be far more accurate at revealing underlying signal structure than prior approaches to time-frequency analysis. In this paper, we have applied HSA to speech and compared to both narrowband and wideband spectrograms. We demonstrate how the AM-FM components, assumed to be intrinsic mode functions, align well with the energy concentrations of the spectrograms and highlight fine structure present in the Hilbert spectrum. As an example, we show never before seen intra-glottal pulse phenomena that are not readily apparent in other analyses. Such fine-scale analyses may have application in speech-based medical diagnosis and automatic speech recognition (ASR) for pathological speakers.

Original languageEnglish (US)
Title of host publication2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages569-575
Number of pages7
ISBN (Print)9781479972913
DOIs
StatePublished - Feb 10 2016
EventIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Scottsdale, United States
Duration: Dec 13 2015Dec 17 2015

Other

OtherIEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015
CountryUnited States
CityScottsdale
Period12/13/1512/17/15

Keywords

  • Hilbert Space
  • Signal Analysis
  • Speech Analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Sandoval, S., De Leon, P. L., & Liss, J. (2016). Hilbert spectral analysis of vowels using intrinsic mode functions. In 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015 - Proceedings (pp. 569-575). [7404846] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASRU.2015.7404846