This paper describes an attempt to extract multiple peripheral features of a point x(ti,fj) on a timespectrum (TS) pattern by observing n´n neighborhoods of the point, and to incorporate these peripheral features (MPFPs: multiple peripheral feature planes) into the feature extractor of a speech recognition system together with MFCC parameters. Two types of peripheral feature extractor, MPFP-KL and MPFP-LR, are proposed. MPFP-KL adopts the orthogonal bases extracted directly from speech data by using KLT of 7x7 blocks on TS patterns. In MPFP-LR, the upper two primal bases are selected and simplified in the form of Δt-operator and Δfoperator obtained by linear regression calculation. MPFP-KL and MPFP-LR show significant improvements in comparison with the standard MFCC feature extractor in experiments with the HMM-based ASR system.
Cite as: Nitta, T., Takigawa, M., Fukuda, T. (2000) A novel feature extraction using multiple acoustic feature planes for HMM-based speech recognition. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 385-388, doi: 10.21437/ICSLP.2000-95
@inproceedings{nitta00_icslp,
author={Tsuneo Nitta and Masashi Takigawa and Takashi Fukuda},
title={{A novel feature extraction using multiple acoustic feature planes for HMM-based speech recognition}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 1, 385-388},
doi={10.21437/ICSLP.2000-95}
}