Probabilistic mixtures provide flexible “universal” approximation of probability density functions. Their wide use is enabled by the availability of a range of efficient estimation algorithms. Among them, quasi-Bayesian estimation plays a prominent role as it runs “naturally” in one-pass mode. This is important in on-line applications and/or extensive databases. It even copes with dynamic natur...

Typical self-organising collective systems consist of a large number of interacting objects that coordinate their activities in a decentralised and often implicit way. Design of such systems is challenging and requires suitable, scalable analysis tools to check properties of proposed system designs before they are put into operation. We present a novel scalable, on-the-fly approximated model-ch...

This paper describes experimentswith a PLSA-based language model for conversational telephone speech. This model uses a long-range history and exploits topic information in the test text to adjust probabilities of test words. The PLSA-based model was found to lower test set perplexity over a traditional word+class-based -gram by 13% (optimistic estimate using a reference transcript as history) ...

This paper proposes an improved approach to extractive summarization of spoken multi-party interaction, in which integrated random walk is performed on a graph constructed on topical/ lexical relations. Each utterance is represented as a node of the graph, and the edges’ weights are computed from the topical similarity between the utterances, evaluated using probabilistic latent semantic analys...

The temporal logics pCTL and pCTL* have been proposed as tools for the formal speci cation and veri cation of probabilistic systems: as they can express quantitative bounds on the probability of system evolutions, they can be used to specify system properties such as reliability and performance. In this paper, we present model-checking algorithms for extensions of pCTL and pCTL* to systems in w...

In this paper we present a probabilistic extension of LOTOS which is upward compatible with LOTOS. We present testing semantics for the reactive and generative models described in vGSST90]. While there is a certain lose of the meaning of probabilities in the reactive model, testing with probabilistic tests proves to be too strong, because it does not relate behavior expressions which we expect ...

This paper describes the combination of a stochastic language model and a formal grammar modelled such as a unification grammar. The stochastic model is trained over 42 million words extracted from Le monde newspaper. The stochastic model is based on smoothed 3-gram and 3-class. The 3-class model is represented by a Markov chain made up of four states. Several experiments have been done to stat...

In this paper, we present a report on the research and development of speech to speech translation system for Asian languages, primarily on the design and implementation of speech recognition and machine translation systems for Indonesia language. As part of the A-STAR project, each participating country will need to develop each component of the full system for the corresponding language. We w...

In human sentence processing, cognitive load can be defined many ways. This report considers a definition of cognitive load in terms of the total probability of structural options that have been disconfirmed at some point in a sentence: the surprisal of word wi given its prefix w0...i−1 on a phrase-structural language model. These loads can be efficiently calculated using a probabilistic Earley...

Recently, it has been shown that probabilistic entailment under coherence is weaker than model-theoretic probabilistic entailment. Moreover, probabilistic entailment under coherence is a generalization of default entailment in System P . In this paper, we continue this line of research by presenting probabilistic generalizations of more sophisticated notions of classical default entailment that...