Time-warping network: a neural approach to hidden Markov model based speech recognition
In: Advances in pattern recognition systems using neural network technologies, Jg. 7 (1993), Heft 4, S. 783-799
academicJournal
- print, 15 ref
Zugriff:
Recently, much interest has been generated regarding speech recognition systems based on Hidden Markov Models (HMMs) and neural network (NN) hybrids. Such systems attempt to combine the best features of both models: the temporal structure of HMMs and the discriminative power of neural networks. In this work we establish one more relation between the HMM and the NN paradigms by introducing the time-warping network (TWN) that is a generalization of both an HMM-based recognizer and a backpropagation net. The basic element of such a network, a time-warping neuron, extends the operation of the formal neuron of a backpropagation network by warping the input pattern to match it optimally to its weights.
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Time-warping network: a neural approach to hidden Markov model based speech recognition
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Autor/in / Beteiligte Person: | LEVIN, E ; PIERACCINI, R ; BOCCHIERI, E |
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Zeitschrift: | Advances in pattern recognition systems using neural network technologies, Jg. 7 (1993), Heft 4, S. 783-799 |
Veröffentlichung: | Singapore: World Scientific, 1993 |
Medientyp: | academicJournal |
Umfang: | print, 15 ref |
ISSN: | 0218-0014 (print) |
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