LREC 2006 - Proceedings sorted by papers

Title	Training Language Models without Appropriate Language Resources: Experiments with an AAC System for Disabled People
Authors	T. Wandmacher, J. Antoine
Abstract	Statistical Language Models (LM) are highly dependent on their training resources. This makes it not only difficult to interpret evaluation results, it also has a deteriorating effect on the use of an LM-based application. This question has already been studied by others. Considering a specific domain (text prediction in a communication aid for handicapped people) we want to address the problem from a different point of view: the influence of the language register. Considering corpora from five different registers, we want to discuss three methods to adapt a language model to its actual language resource ultimately reducing the effect of training dependency: (a) A simple cache model augmenting the probability of the n last inserted words; (b) a user dictionary, keeping every unseen word; and (c) a combined LM interpolating a base model with a dynamically updated user model. Our evaluation is based on the results obtained from a text prediction system working on a trigram LM.
Keywords	Language Models, Adaptation, Text Prediction, Augmentative and Alternative Communication.
Full paper	Training Language Models without Appropriate Language Resources: Experiments with an AAC System for Disabled People

Title

Training Language Models without Appropriate Language Resources: Experiments with an AAC System for Disabled People

Authors

T. Wandmacher, J. Antoine

Abstract

Statistical Language Models (LM) are highly dependent on their training resources. This makes it not only difficult to interpret evaluation results, it also has a deteriorating effect on the use of an LM-based application. This question has already been studied by others. Considering a specific domain (text prediction in a communication aid for handicapped people) we want to address the problem from a different point of view: the influence of the language register. Considering corpora from five different registers, we want to discuss three methods to adapt a language model to its actual language resource ultimately reducing the effect of training dependency: (a) A simple cache model augmenting the probability of the n last inserted words; (b) a user dictionary, keeping every unseen word; and (c) a combined LM interpolating a base model with a dynamically updated user model. Our evaluation is based on the results obtained from a text prediction system working on a trigram LM.

Keywords

Language Models, Adaptation, Text Prediction, Augmentative and Alternative Communication.

Full paper

Training Language Models without Appropriate Language Resources: Experiments with an AAC System for Disabled People