Fusing acoustic feature representations for computational paralinguistics tasks

Heysem Kaya, Alexey A. Karpov

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The field of Computational Paralinguistics is rapidly growing and is of interest in various application domains ranging from biomedical engineering to forensics. The INTERSPEECH ComParE challenge series has a field-leading role, introducing novel problems with a common benchmark protocol for comparability. In this work, we tackle all three ComParE 2016 Challenge corpora (Native Language, Sincerity and Deception) benefiting from multi-level normalization on features followed by fast and robust kernel learning methods. Moreover, we employ computer vision inspired low level descriptor representation methods such as the Fisher vector encoding. After nonlinear preprocessing, obtained Fisher vectors are kernelized and mapped to target variables by classifiers based on Kernel Extreme Learning Machines and Partial Least Squares regression. We finally combine predictions of models trained on popularly used functional based descriptor encoding (openSMILE features) with those obtained from the Fisher vector encoding. In the preliminary experiments, our approach has significantly outperformed the baseline systems for Native Language and Sincerity sub-challenges both in the development and test sets.

Original languageEnglish
Title of host publicationINTERSPEECH-2016
Pages2046-2050
Number of pages5
Volume08-12-September-2016
DOIs
Publication statusPublished - 1 Sept 2016
Event17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 - San Francisco, United States
Duration: 8 Sept 201616 Sept 2016

Publication series

NameProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
ISSN (Print)2308-457X

Conference

Conference17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016
Country/TerritoryUnited States
CitySan Francisco
Period8/09/1616/09/16

Keywords

  • ComParE
  • Computational paralinguistics
  • ELM
  • Fisher vector
  • Native Language
  • PLS
  • Sincerity

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