Subspace pursuit method for kernel-log-linear models

Yotaro Kubo, Simon Wiesler, Ralf Schlueter, Hermann Ney, Shinji Watanabe, Atsushi Nakamura, Tetsunori Kobayashi

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

5 Citations (Scopus)

Abstract

This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, log-linear models without mixtures have been used as emission probability density functions in hidden Markov models for automatic speech recognition. In that framework, nonlinearly-transformed high-dimensional features are used to achieve the nonlinear classification of the original observation vectors without using mixtures. In this paper, with the goal of using high-dimensional features in kernel spaces, the cutting plane subspace pursuit method proposed for support vector machines is generalized and applied to log-linear models. The experimental results show that the proposed method achieved an efficient approximation of the feature space by using a limited number of basis vectors.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages4500-4503
Number of pages4
DOIs
Publication statusPublished - 2011 Aug 18
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: 2011 May 222011 May 27

Publication series

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

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
CountryCzech Republic
CityPrague
Period11/5/2211/5/27

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Keywords

  • Automatic speech recognition
  • dimensionality reduction
  • kernel method
  • log-linear model
  • subspace method

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Kubo, Y., Wiesler, S., Schlueter, R., Ney, H., Watanabe, S., Nakamura, A., & Kobayashi, T. (2011). Subspace pursuit method for kernel-log-linear models. In 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings (pp. 4500-4503). [5947354] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2011.5947354