ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Confusion-based entropy-weighted decoding for robust speech recognition

Yi Chen, Chia-yu Wan, Lin-shan Lee

An entropy-based feature parameter weighting scheme was proposed previously [1], in which the scores obtained from different feature parameters are weighted differently in the decoding process according to an entropy measure. In this paper, we propose a more delicate entropy measure for this purpose considering the inherent confusion among different acoustic classes. If a set of acoustic classes are easily confused, those feature parameters which can distinguish them should be emphasized. Extensive experiments with the Aurora 2 testing environment verified that this approach is equally useful for different types of features, and can be easily integrated with typical existing robust speech recognition approaches.

Y. Chen, C.-Y. Wan, L.-S. Lee, "Entropy-Based Feature Parameter Weighting for Robust Speech Recognition," ICASSP 2006.


doi: 10.21437/Interspeech.2008-293

Cite as: Chen, Y., Wan, C.-y., Lee, L.-s. (2008) Confusion-based entropy-weighted decoding for robust speech recognition. Proc. Interspeech 2008, 1008-1011, doi: 10.21437/Interspeech.2008-293

@inproceedings{chen08c_interspeech,
  author={Yi Chen and Chia-yu Wan and Lin-shan Lee},
  title={{Confusion-based entropy-weighted decoding for robust speech recognition}},
  year=2008,
  booktitle={Proc. Interspeech 2008},
  pages={1008--1011},
  doi={10.21437/Interspeech.2008-293}
}