Two methods to correct phonemic transcriptions produced by the acoustic processor of a speech recognition system are described and compared. The first method that was invented by Prof. Teuvo Kohonen and named the Dynamically Expanding Context (DEC), involves a large set of error-correcting rules automatically constructed from examples. This symbolic approach is compared with a connectionist one, which employs a multi-layered feed-forward network trained with back propagation. Our experiments demonstrate that the latter paradigm is far from optimal when context-dependent mapping (e.g. correction) from one set of symbol strings to another is desired. The DEC-method is shown to have better correction capabilities. Beside this, the training time required by DEC is a fraction of that required by back propagation.
Cite as: Torkkola, K., Raivio, K. (1989) Comparison of symbolic and connectionist approaches to eliminate coarticulation effects in phonemic speech recognition. Proc. First European Conference on Speech Communication and Technology (Eurospeech 1989), 1009-1012, doi: 10.21437/Eurospeech.1989-2
@inproceedings{torkkola89_eurospeech,
author={Kari Torkkola and Kimmo Raivio},
title={{Comparison of symbolic and connectionist approaches to eliminate coarticulation effects in phonemic speech recognition}},
year=1989,
booktitle={Proc. First European Conference on Speech Communication and Technology (Eurospeech 1989)},
pages={1009--1012},
doi={10.21437/Eurospeech.1989-2}
}