Large vocabulary recognition using linked predictive neural networks

A large-vocabulary isolated word recognition system based on linked predictive neural networks (LPNNs) is presented. In this system, neural networks are used as predictors of speech frames, enabling a pool of such networks to serve as phoneme models. Higher-level algorithms are used to organize these networks, linking them into sequences corresponding to the phonetic spellings of words, and to train and evaluate the networks for word recognition. By virtue of linking phonemic networks, the LPNN is vocabulary independent and can be applied to large-vocabulary recognition. Recognition rates of 94% for a 234-word Japanese vocabulary of acoustically similar words and 90% for a larger vocabulary of 924 words are obtained