Radial Basis Functions for Speech Recognition
the purpose of this paper is to study the application of Radial Basis Functions (RBF) to automatic speech recognition. Results of several experiments with these networks on the recognition of phonemes for the TIMIT database are presented, including an experiment on a recurrent network of RBFs.
Unable to display preview. Download preview PDF.
- 1.Bengio Y., Cardin R., De Mori R. & Merlo E. (1989a), “Programmable Execution of Multi-Layered Networks for Automatic Speech Recognition”, in Communications of the Association of Computing Machinery, February 1989, vol. 32, number 2, pp. 195–199.Google Scholar
- 2.Bengio Y., Gori M. & De Mori R. (1989c), “BPS: a Learning Algorithm for Capturing the Dynamic Nature of Speech”, in the Proceedings of the International Joint Conference on Neural Networks 1989, pp. II–417 – II-424.Google Scholar
- 4.Bengio Y., Cardin R., De Mori R. (1990), “Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge”, in Advances in Neural Information Processing Systems 2, ed. D.S. Touretzky, Morgan Kaufmann Publishers.Google Scholar
- 6.Garofolo J.S. (1988), “Getting started with the DARPA TIMIT CD-ROM: an acoustic phonetic continuous speech database”, National Institute of Standards and Technology (NIST), Gaithersburgh, MD.Google Scholar
- 7.Kruschke J.K. (1990), “ALCOVE: a connectionist model of category learning”, Technical Report 19, Cognitive Science Program, Indiana University.Google Scholar
- 9.Leung H.C. & Zue V. (1990), “Phonetic classification using multi-layered perceptrons”, ICASSP 90, pp.525–528.Google Scholar
- 10.Mel B.W. & Koch C. (1990), “Sigma-Pi Learning: A Model for Associative Learning in Cerebral Cortex”, Advances in Neural Networks Information Processing Systems 2, ed. D.S. Touretzky, Morgan Kauffman.Google Scholar
- 13.Poggio T. & Girosi F. (1989), “A Theory of Networks for Approximation and Learning”, MIT A.I. Memo No. 1140.Google Scholar
- 14.Robinson T. & Fallside F. (1990), “Phoneme recognition from the TIMIT database using recurrent error propagation networks”, CUED/F-INFEG/TR.42, Cambridge University Engineering dept.Google Scholar
- 15.Rumelhart D.E., Hinton G., Williams R.J. (1986), “Learning internal representation by error propagation”, in Parallel Distributed Processing, vol. 1, (eds. Rumelhart & McClelland), Bradford Books/MIT Press.Google Scholar
- 16.Waibel A., Hanazawa T., Hinton G., Shikano K. & Lang K. (1987), “Phoneme Recognition using Time Delay Neural Networks”, Technical Report TR-I-0006, ATR Interpreting Telephony Research Laboratories.Google Scholar