Over the past decade or so, several advances have been made to the design of modern
large vocabulary continuous speech recognition (LVCSR) systems to the point where their …

Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular
tools for summarization and manifold discovery in discrete data. However, LDA does not …

(57) ABSTRACT A method and system for multimodal human-vehicle inter action including
receiving input from an occupant in a vehicle via more than one mode and performing …

There is a vast body of literature on LVCSR research and some limitation is necessary in the
scope of this article. We will focus primarily on the techniques that have been successful in …

This paper addresses the issue of language model adaptation for Recurrent Neural Network
Language Models (rnnlm s), which have recently emerged as a state-of-the-art method for …

Latent Dirichlet allocation (LDA) was successfully developed for document modeling due to
its generalization to unseen documents through the latent topic modeling. LDA calculates …

Statistical language models (LM) play a key role in Automatic Speech Recognition (ASR)
systems used by conversational agents. These ASR systems should provide a high …

Probabilistic models are often viewed as insufficiently expressive because of strong
limitation and assumption on the probabilistic distribution and the fixed model complexity …

Abstract We integrated the Latent Dirichlet Allocation (LDA) approach, a latent semantic
analysis model, into unsupervised language model adaptation framework. We adapted a …

Recent years have seen a surge in accounts motivated by information theory that consider
language production to be partially driven by a preference for communicative efficiency …