In this paper we propose an algorithm for efficient compression of feature extracted parameters used in speech recognition. The algorithm provides a compression ratio of roughly 1:10 and causes negligible or no loss in recognition performance. It is also shown to be robust against enviromental noise. Combined with an appropriate framing structure, a complete system is obtained, which can be used for implementing speech recognition applications e.g. in a cellular mobile environment. The system achieves a gross bitrate as low as 4200 bps.
Cite as: Kiss, I., Kapanen, P. (1999) Robust feature vector compression algorithm for distributed speech recognition. Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999), 2183-2186, doi: 10.21437/Eurospeech.1999-483
@inproceedings{kiss99_eurospeech,
author={Imre Kiss and Pekka Kapanen},
title={{Robust feature vector compression algorithm for distributed speech recognition}},
year=1999,
booktitle={Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999)},
pages={2183--2186},
doi={10.21437/Eurospeech.1999-483}
}