In this paper, we describe automatic speech recognition system where features extracted from human speech production system in form of articulatory movements data are effectively integrated in the acoustic model for improved recognition performance. The system is based on the hybrid HMM/BN model, which allows for easy integration of different speech features by modeling probabilistic dependencies between them. In addition, features like articulatory movements, which are difficult or impossible to obtain during recognition, can be left hidden, in fact eliminating the need of their extraction. The system was evaluated in phoneme recognition task on small database consisting of three speakers' data in speaker dependent and multi-speaker modes. In both cases, we obtained higher recognition rates compared to conventional, spectrum based HMM system with the same number of parameters.
Cite as: Markov, K., Dang, J., Iizuka, Y., Nakamura, S. (2003) Hybrid HMM/BN ASR system integrating spectrum and articulatory features. Proc. 8th European Conference on Speech Communication and Technology (Eurospeech 2003), 965-968, doi: 10.21437/Eurospeech.2003-334
@inproceedings{markov03_eurospeech,
author={Konstantin Markov and Jianwu Dang and Yosuke Iizuka and Satoshi Nakamura},
title={{Hybrid HMM/BN ASR system integrating spectrum and articulatory features}},
year=2003,
booktitle={Proc. 8th European Conference on Speech Communication and Technology (Eurospeech 2003)},
pages={965--968},
doi={10.21437/Eurospeech.2003-334}
}