What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Conversations abound with uncertainties of various kinds. Treating conversation as inference and decision making under uncertainty, we propose a task independent, multimodal archi...
We present a phrasal synchronous grammar model of translational equivalence. Unlike previous approaches, we do not resort to heuristics or constraints from a word-alignment model,...
Phil Blunsom, Trevor Cohn, Chris Dyer, Miles Osbor...
We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic late...
In this paper, models and algorithms are presented for transcription of pitch and timings in polyphonic music extracts, focusing on the algorithm details of the sequential Markov ...