Discriminative feature transforms using differenced maximum mutual information

Marc Delcroix, Atsunori Ogawa, Shinji Watanabe, Tomohiro Nakatani, Atsushi Nakamura

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

4 Citations (Scopus)

Abstract

Recently feature compensation techniques that train feature transforms using a discriminative criterion have attracted much interest in the speech recognition community. Typically, the acoustic feature space is modeled by a Gaussian mixture model (GMM), and a feature transform is assigned to each Gaussian of the GMM. Feature compensation is then performed by transforming features using the transformation associated with each Gaussian, then summing up the transformed features weighted by the posterior probability of each Gaussian. Several discriminative criteria have been investigated for estimating the feature transformation parameters including maximum mutual information (MMI) and minimum phone error (MPE). Recently, the differenced MMI (dMMI) criterion that generalizes MMI andMPE, has been shown to provide competitive performance for acoustic model training. In this paper, we investigate the use of the dMMI criterion for discriminative feature transforms and demonstrate in a noisy speech recognition experiment that dMMI achieves recognition performance superior to that of MMI or MPE.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages4753-4756
Number of pages4
DOIs
Publication statusPublished - 2012 Oct 23
Externally publishedYes
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: 2012 Mar 252012 Mar 30

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
CountryJapan
CityKyoto
Period12/3/2512/3/30

Keywords

  • Speech recognition
  • differenced MMI
  • discriminative feature transforms
  • discriminative training

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Delcroix, M., Ogawa, A., Watanabe, S., Nakatani, T., & Nakamura, A. (2012). Discriminative feature transforms using differenced maximum mutual information. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 4753-4756). [6288981] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2012.6288981