Abstract
In a continuous speech recognizer, the recognition problem is usually modelled as a search for the best path in a network of transitions between states. A full search can be very expensive in terms of computation and storage requirements. By adopting a segment based rather than a frame based approach,one can already obtain a severe reduction of mese requirements, but this may not be sufficient to allow for real time recognition. For our segment based Neural Network / Dynamic Programming hybrid [1], we have therefore introduced a heuristic search method. It is shown that this search is significantly faster than a Viterbi beam search, while there is no degradation of the recognition results.
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References
[1] J.P. Martens, A. Vorstermans, N. Cremelie (1993), “A new Dynamic Programming / Multi-Layer Perceptron Hybrid for continuous speech recognition”, in Proceedings of EUROSPEECH-93, Berlin.
[2] N J. Nilsson (1980), Principles of Artificial Intelligence, Palo Alto, California: Tioga.
[3] H. Ney (1992), “A comparative Study of Two Search Strategies for Connected Word Recognition: Dynamic Programming and Heuristic Search”, in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 5, May 1992.
[4] D.B. Paul (1992), “An Efficient A* Stack Decoder Algorithm for Continuous Speech Recognition with a Stochastic Language Model,” in Proceedings of ICASSP-92, San Francisco.
[5] S. Austin, R. Schwartz and P. Placeway (1991), “The Forward-Backward Search Algorithm,” in Proceedings of ICASSP-91 Toronto.
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© 1995 Springer-Verlag Berlin Heidelberg
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Cremelie, N., Martens, JP. (1995). Heuristic Search Methods for a Segment Based Continuous Speech Recognizer. In: Ayuso, A.J.R., Soler, J.M.L. (eds) Speech Recognition and Coding. NATO ASI Series, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-57745-1_6
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DOI: https://doi.org/10.1007/978-3-642-57745-1_6
Publisher Name: Springer, Berlin, Heidelberg
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