User profiling through spoken utterances for user specific service

Minseok Keum, David K. Han, Hanseok Ko

Research output: Contribution to conferencePaper

Abstract

For providing user specific services in vehicle environment, we propose a speech based interface that identifies gender, age, and language of a user during speech utterances. For gender and age recognition, physiological factors are important discriminative information. However, for language recognition, phonotactics in addition to spectral information is exploited. All of the above schemes are evaluated using Mel-Frequency Cepstral Coefficient (MFCC) based features and Gaussian Mixture Models (GMM). We also evaluate the effectiveness of channel compensation techniques such as Cepstral Mean Subtraction (CMS) and RASTA filtering. As a conclusion we suggest that MFCC based feature can effectively be applied to the speech related recognition problems.

Original languageEnglish
Publication statusPublished - 2011
Event5th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, DSP 2011 - Kiel, Germany
Duration: 2011 Sep 42011 Sep 7

Other

Other5th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, DSP 2011
CountryGermany
CityKiel
Period11/9/411/9/7

Keywords

  • Cepstral-Time Matrix (CTM)
  • Channel compensation
  • Gaussian Mixture Models (GMM)
  • Mel-Frequency Cepstral Coefficient (MFCC)
  • Speech user profiling

ASJC Scopus subject areas

  • Signal Processing
  • Automotive Engineering

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  • Cite this

    Keum, M., Han, D. K., & Ko, H. (2011). User profiling through spoken utterances for user specific service. Paper presented at 5th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, DSP 2011, Kiel, Germany.