Computational model of speech understanding

Authors:
Daniel Nehme Müller;Philippe O. A. Navaux
Affiliations:
Institute of Informatics, The Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil;Institute of Informatics, The Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
Venue:
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Year:
2006

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Abstract

This paper proposes a speech comprehension computational model based on neurocognitive researches. The computational representation uses techniques as wavelets transform and connectionist models. The speech signal codification and data prosodic extraction are derived from wavelet coefficients. Moreover, the connectionist models are used to perform syntactic parsing and prosodic-semantic mapping. Thus, the computational model applies three approaches: the application of wavelet coefficients as input in connectionist language analysis, the use of SARDSRN-RAAM system to syntactic analysis as well as the proposition of prosodic-semantic maps to language contexts definition.