Statistical language models play a major role in current speech recognition systems. Most of these models have focussed on relatively local interactions between words. Recently, h...
We investigate a recently proposed Bayesian adaptation method for building style-adapted maximum entropy language models for speech recognition, given a large corpus of written la...
Neural network language models (NNLM) have become an increasingly popular choice for large vocabulary continuous speech recognition (LVCSR) tasks, due to their inherent generalisa...
Junho Park, Xunying Liu, Mark J. F. Gales, Philip ...
We present an integrated approach to speech and natural language processing which uses a single parser to create training for a statistical speech recognition component and for in...
In language modeling for speech recognition, both the amount of training data and the match to the target task impact the goodness of the model, with the trade-off usually favorin...
Marius A. Marin, Sergey Feldman, Mari Ostendorf, M...