Speech Recognition Experiments with Perceptrons

Part of Neural Information Processing Systems 0 (NIPS 1987)

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David Burr


Artificial neural networks (ANNs) are capable of accurate recognition of simple speech vocabularies such as isolated digits [1]. This paper looks at two more difficult vocabularies, the alphabetic E-set and a set of polysyllabic words. The E-set is difficult because it contains weak discriminants and polysyllables are difficult because of timing variation. Polysyllabic word recognition is aided by a time pre-alignment technique based on dynamic pro(cid:173) gramming and E-set recognition is improved by focusing attention. Recogni(cid:173) tion accuracies are better than 98% for both vocabularies when implemented with a single layer perceptron.