|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
A NEURAL NETWORK BASED, SPEAKER INDEPENDENT, LARGE VOCABULARY, CONTINUOUS SPEECH RECOGNITION SYSTEM: THE WERNICKE PROJECT
A. J. Robinson, L. Almeida, J.-M. Boite, H. Bourlard, F. Fallside, M. Hochberg, D. Kershaw, P. Kohn, Y. Konig, N. Morgan, J. P. Neto, S. Renals, M. Saerens and C. Wooters
This paper describes the research underway for the ESPRIT WERNICKE project. The project brings together a number of different groups from Europe and the US and focuses on extending the state-of-the-art for hybrid hidden Markov model/connectionist approaches to large vocabulary, continuous speech recognition. This paper describes the specific goals of the research and presents the work performed to date. Results are reported for the resource management talker-independent recognition task. The paper concludes with a discussion of the projected future work.
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