Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …

In this paper, we present a survey on the application of recurrent neural networks to the task
of statistical language modeling. Although it has been shown that these models obtain good …

Many groups have investigated the relationship of word error rate and perplexity of
language models. This issue is of central interest because perplexity optimization can be …

The most widely-used evaluation metric for language models for speech recognition is the
perplexity of test data. While perplexities can be calculated efficiently and without access to …

Log-Linear Interpolation Of Language Models Page 1 LOG-LINEAR INTERPOLATION OF
LANGUAGE MODELS Dietrich Klakow Philips GmbH Forschungslaboratorien, Wei hausstr.2 …

In the rapidly evolving field of machine learning, training models with datasets from various
locations and organizations presents significant challenges due to privacy and legal …

This paper presents a study of using neural probabilistic models in a syntactic based
language model. The neural probabilistic model makes use of a distributed representation of …

Current evaluation metrics for language modeling and generation rely heavily on the
accuracy of predicted (or generated) words as compared to a reference ground truth. While …

This article describes a methodology for collecting text from the Web to match a target
sublanguage both in style (register) and topic. Unlike other work that estimates n-gram …

Language models (LM) for interactive speech recognition systems are trained on large
amounts of data and the model parameters are optimized on past user data. New …