Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation

Part of Advances in Neural Information Processing Systems 4 (NIPS 1991)

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Yoshua Bengio, Renato De Mori, Giovanni Flammia, Ralf Kompe


The subject of this paper is the integration of multi-layered Artificial Neu(cid:173) ral Networks (ANN) with probability density functions such as Gaussian mixtures found in continuous density Hidden Markov Models (HMM). In the first part of this paper we present an ANN/HMM hybrid in which all the parameters of the the system are simultaneously optimized with respect to a single criterion. In the second part of this paper, we study the relationship between the density of the inputs of the network and the density of the outputs of the networks. A few experiments are presented to explore how to perform density estimation with ANNs.