Statistical language models are widely used in automatic speech recognition in order to constrain the decoding of a sentence. Most of these models derive from the classical n-gram paradigm. However, the production of a word depends on a large set of linguistic features : lexical, syntactic, semantic, etc. Moreover, in some natural languages the gender and number of the left context affect the p...

Statistical model-checking is a recent technique used for both verification and performance analysis of hybrid systems. It does not suffer from decidability issues or state-space explosion compared to traditional model-checking. Furthermore, it is applicable to more powerful formalisms such as stochastic hybrid automata. Its principle is simple so how simple is it really to make it work in prac...

In this article, we discuss the statistical model of the wireless channel in reasonable detail. We start with the most intuitive model of the time-varying channel and derive statistical parameters which are used to characterise reallife channels. We derive both the first and second order statistics and indicate their physical significance.

This paper makes the case for developing a statistical model to describe the behavior of the residuals between model estimates and corresponding observations. Using a framework that relates model estimates to corresponding observations, we show that the distribution of the residuals can be conveniently characterized by the geometric mean, mg, and the geometric standard deviation, sg, of the rat...

In a fully collaborative, mixed-initiative dialogue it is necessary to both interpret and generate nominal descriptions and so the question of the extent to which these processes can share knowledge is helpful for deciding what to include in the dialogue history and for gaining insight for generation into what enhances interpretation and vice versa. Although theoretical and symbolic models for ...

STATISTICAL MODELS AND ANALYSIS TECHNIQUES FOR LEARNING IN RELATIONAL DATA