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2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
Recently there has been increasing interest in using neural networks for language modeling. In contrast to the well known backoff n-gram language models, the neural network approach tries to limit the data sparseness problem by performing the estimation in a continuous space, allowing by this means smooth interpolations. The complexity to train such a model and to calculate one n-gram probability is however several orders of magnitude higher than for the backoff models, making the new approachdoi:10.1109/ijcnn.2004.1381158 fatcat:pm2vjwt2q5aonmsfnfytj6z2qy