The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Connectionist architectural learning for high performance character and speech recognition
Abstract
The authors applied an automatic structure optimization (ASO) algorithm to the optimization of multistate time-delay neural networks (MSTDNNs), an extension of the TDNN. These networks allow the recognition of sequences of ordered events that have to be observed jointly. For example, in many speech recognition systems the recognition of words is decomposed into the recognition of sequences of phonemes or phonemelike units. In handwritten character recognition the recognition of characters can be decomposed into the joined recognition of characteristic strokes, etc. The combination of the proposed ASO algorithm with the MSTDNN was applied successfully to speech recognition and handwritten character recognition tasks with varying amounts of training data.>
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“On the other hand, GTN's extend HMM's by allowing to combine in a well-principled framework multiple levels of processing, or multiple models (e.g., Pereira et al. have been using the transducer framework for stacking HMM's representing different levels of processing in automatic speech recognition [86]).”
From Gradient-based learning applied to document recognition (1998) · cites this paper as [86]
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“The idea of transforming graphs into other graphs has received considerable attention in computer science through the concept of weighted finite-state transducers [86].”
From Gradient-based learning applied to document recognition (1998) · cites this paper as [86]
Citations
Cites
Phoneme recognition using time-delay neural networks
Waibel, A., Hanazawa, T., Hinton, G., Shikano, K., & Lang, K. J. (1989) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/29.21701 · Cited by 2,643
Research works printed but not linked: 9
- 10.1016/0031-3203(91)90081-F · DOI
- haffner, 0, Time-Delay Neural Networks Embedding Time Alignment: A Performance Analysis, Eurospeech-91
- moody, 1991, The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems, Advances in neural information processing systems, 4
- 10.1162/neco.1989.1.1.151 · DOI
- 10.1109/ICNN.1993.298800 · DOI
- 10.1109/TASSP.1978.1163055 · DOI · Paper page
- 10.1109/ICASSP.1991.150289 · DOI
- weigend, 1990, Predicting the future A connectionist approach
- 10.1109/ICASSP.1989.266376 · DOI
Cited by
Sorted by citations
Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805
Metadata
- Authors
- Bodenhausen, U., & Manke, S.
- Affiliations
- Karlsruhe Institute of Technology (DE)
- Venue
- IEEE International Conference on Acoustics Speech and Signal Processing
- Publisher
- IEEE
- Published
- 1993
- Volume
- 4
- Pages
- 625-628 vol.1
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2132904398
- Cited by
- 18
- References
- 1
- Citations by year
- 2015: 1 · 2014: 1
- FWCI
- 2.46
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Acoustics Speech and Signal Processing (publishedVersion)
- Repository KITopen (Karlsruhe Institute of Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Handwritten Text Recognition Techniques
- Keywords
- time-delay neural networks, speech recognition, handwritten character recognition, limited training data
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