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Learning and Plan Refinement in a Knowledge-Based System for Automatic Speech Recognition
February 1987 (vol. 9 no. 2)
pp. 289-305
Renato De Mori, School of Computer Science, McGill University, Montreal, P. Q. H3A 2K6, Canada.
Lily Lam, Department of Computer Science, Concordia University, Montreal, P.Q. H3G 1M8, Canada.
Michel Gilloux, Centre National d'Etudes de Telecommunications, B. P. 40, Lannion 22301, France.
This paper shows how a semiautomatic design of a speech recognition system can be done as a planning activity. Recognition performances are used for deciding plan refinement. Inductive learning is performed for setting action preconditions. Experimental results in the recognition of connected letters spoken by 100 speakers are presented.
Citation:
Renato De Mori, Lily Lam, Michel Gilloux, "Learning and Plan Refinement in a Knowledge-Based System for Automatic Speech Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 2, pp. 289-305, Feb. 1987, doi:10.1109/TPAMI.1987.4767902
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