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Validation techniques for parallel feature streams: the case of phoneme identification for speech recognition

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Aioanei D. , Neugebauer M. , Carson-Berndsen J.

2005

tom Vol. 15, no. 3

279--290

This paper presents an approach to the phonetic interpretation of multilinear feature representations of speech utterances combining linguistic knowledge and efficient computational techniques. Multilinear feature representations are processed as intervals and the linguistic knowledge used by the system takes the form of feature implication rules (constraints) represented as subsumption hierarchies which are used to validate each interval. In the case of noisy or underspecified data, the linguistic constraints can be used to enrich the representations. Experiments are also presented to show that the system is logically correct and does not introduce errors in the data, and that it deals with underspecified and noisy input.