In this paper, we propose a new method for computing and applying language model look-ahead in a dynamic network decoder, exploiting the sparseness of backing-off n-gram language ...
In this paper we investigate random forest based language model adaptation. Large amounts of out-of-domain data are used to grow the decision trees while very small amounts of in-...
In this work we present the Subsequence Similarity Language Model (S2-LM) which is a new approach to language modeling based on string similarity. As a language model, S2-LM gener...
From the perspective of the linguist, the theory of formal languages serves as an abstract model to address issues such as complexity, learnability, information content, etc. which...
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...