Parallel neural networks for speech recognition

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 4, Issue , 1997, Pages 2093-2097

  Lee, Byouing Jik ^a  

^a UNIVERSITY OF IOWA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX COMPUTATION; COMPLEX PROBLEMS; LETTER RECOGNITION; LOCAL MINIMA PROBLEMS; MULTILAYERED NEURAL NETWORKS; PARALLEL NEURAL NETWORKS; SEARCH SPACES; TRAINING DATA;

COMPLEX NETWORKS; SPEECH RECOGNITION; COMPUTATIONAL COMPLEXITY; NEURAL NETWORKS; PARALLEL PROCESSING SYSTEMS; SPEECH ANALYSIS;

NEURAL NETWORKS; SPEECH RECOGNITION;

PARALLEL NEURAL NETWORKS BY CONFIDENCE (PNNC); PARALLEL NEURAL NETWORKS BY SUCCESS/FAILURE (PNNS);

EID: 0030650648     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614227     Document Type: Conference Paper

References (11)

1. P. K. Chan and S. J. Stolfo. A comparative evaluation of voting and meta-learning on partitioned data. In International Conference on Machine Learning, volume 5, pages 42-49, 1995.
2. H. Drucker, R. Schapire, and P. Simard. Improving performance in neural networks using a boosting algorithm. Advances an Neural Information Processing Systems, 5, 1993.
3. S. E. Fahlman and C. Lebiere. The cascade-correlation learning architecture. Advances in Neural Information Processing Systems, 2~524-532, 1990.
4. Z. Hertz, A. Krogh, and R. Palmer. Introduction to the theory of Neural Computation. Addison Wesley, 1990.
5. Y. LeCun. Optimal brain damage. Advances in Neural Information Processing Systems, 3:598-605, 1991.
6. B. J. Lee. Speech recognition using neural networks (hearnet): Mapping from a set of phoneme strings to characterlword recognition. Intelligent Systems, E. A. Yfantis (Ed. ), 1:525-530, 1995.
7. R. P. Lippman. Review of neural networks for speech recognition. Neural Computation, 1:l-38, 1989.
8. D. B. Parker. Optimal algorithms for adaptive networks: second order back propagation, second order hebbian learning. In IEEE First Annual Conference on Neural Networks, June 1987.
9. D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning internal representations by backpropagation. Parallel Distributed Processing, 1:318-362, 1986.
10. R. Schapire. The strength of weak learnability. Machine Learning, 5(2):197-227, 1990.
11. T. J. Sejnowski and C. R. Rosenberg. Parallel networks that learn to pronounce ienglish text. Complex Systems, 1(1):145-168, 1987.