Subspace pursuit method for kernel-log-linear models

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

研究成果: Conference contribution

5 引用 (Scopus)

抜粋

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.

元の言語English
ホスト出版物のタイトル2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
ページ4500-4503
ページ数4
DOI
出版物ステータスPublished - 2011 8 18
イベント36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
継続期間: 2011 5 222011 5 27

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷物)1520-6149

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Czech Republic
Prague
期間11/5/2211/5/27

    フィンガープリント

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

これを引用

Kubo, Y., Wiesler, S., Schlueter, R., Ney, H., Watanabe, S., Nakamura, A., & Kobayashi, T. (2011). Subspace pursuit method for kernel-log-linear models. : 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