This paper describes an incremental approach to parsing transcribed spontaneous speech containing disfluencies with a Hierarchical Hidden Markov Model (HHMM). This model makes use...
Structural information about a document is essential for structured query processing, indexing, and retrieval. A document page can be partitioned into a hierarchy of homogeneous r...
We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts sur...
This paper explains how Partially Observable Markov Decision Processes (POMDPs) can provide a principled mathematical framework for modelling the inherent uncertainty in spoken di...
Steve Young, Milica Gasic, Simon Keizer, Fran&cced...
This paper investigates the decentralized detection of Hidden Markov Processes using the NeymanPearson test. We consider a network formed by a large number of distributed sensors....
Joffrey Villard, Pascal Bianchi, Eric Moulines, Pa...