Analytic Filter Bank for Speech Analysis, Feature Extraction and Perceptual Studies

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Abstract

Speech signal consists of events in time and frequency, and therefore its analysis with high-resolution time-frequency tools is often of importance. Analytic filter bank provides a simple, fast, and flexible method to construct time-frequency representations of signals. Its parameters can be easily adapted to different situations from uniform to any auditory frequency scale, or even to a focused resolution. Since the Hilbert magnitude values of the channels are obtained at every sample, it provides a practical tool for a high-resolution time-frequency analysis.

The present study describes the basic theory of analytic filters and tests their main properties. Applications of analytic filter bank to different speech analysis tasks including pitch period estimation and pitch synchronous analysis of formant frequencies and bandwidths are demonstrated. In addition, a new feature vector called group delay vector is introduced. It is shown that this representation provides comparable, or even better results, than those obtained by spectral magnitude feature vectors in the analysis and classification of vowels. The implications of this observation are discussed also from the speech perception point of view.
Original languageEnglish
Title of host publicationProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
PublisherInternational Speech Communication Association
Pages449-453
Number of pages5
Volume2017-August
ISBN (Print)978-1-5108-4876-4
DOIs
Publication statusPublished - Aug 2017
MoE publication typeA4 Article in a conference publication
EventInterspeech - Stockholm, Sweden
Duration: 20 Aug 201724 Aug 2017
Conference number: 18
http://www.interspeech2017.org/

Publication series

NameInterspeech: Annual Conference of the International Speech Communication Association
ISSN (Electronic)1990-9772

Conference

ConferenceInterspeech
CountrySweden
CityStockholm
Period20/08/201724/08/2017
Internet address

Keywords

  • speech analysis
  • pitch-synchronous analysis
  • time-frequency methods

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