12 citations · 29 across the 6 of their papers we have counts for
6 papers
Towards an Improved Performance Measure for Language Models
Joerg P. Ueberla
In this paper a first attempt at deriving an improved performance measure for language models, the probability ratio measure (PRM) is described. In a proof of concept experiment, i…
Domain Adaptation with Clustered Language Models
Joerg P. Ueberla
In this paper, a method of domain adaptation for clustered language models is developed. It is based on a previously developed clustering algorithm, but with a modified optimisatio…
Clustered Language Models with Context-Equivalent States
J. P. Ueberla, I. R. Gransden
In this paper, a hierarchical context definition is added to an existing clustering algorithm in order to increase its robustness. The resulting algorithm, which clusters contexts…
An Extended Clustering Algorithm for Statistical Language Models
Joerg P. Ueberla
Statistical language models frequently suffer from a lack of training data. This problem can be alleviated by clustering, because it reduces the number of free parameters that need…
On Using Selectional Restriction in Language Models for Speech Recognition
Joerg P. Ueberla
In this paper, we investigate the use of selectional restriction -- the constraints a predicate imposes on its arguments -- in a language model for speech recognition. We use an un…
Analyzing and Improving Statistical Language Models for Speech Recognition
Joerg P. Ueberla
In many current speech recognizers, a statistical language model is used to indicate how likely it is that a certain word will be spoken next, given the words recognized so far. Ho…