We propose a distribution-based pruning of n-gram backoff language models. Instead of the conventional approach of pruning n-grams that are infrequent in training data, we prune n...
The PECO framework is a knowledge representation for formulating clinical questions. Queries are decomposed into four aspects, which are Patient-Problem (P), Exposure (E), Compari...
We investigate the automatic labelling of “events” from an audio recording of a sports game. We describe a technique that utilises a hierarchy of language models, which are a ...
Shrinkage-based exponential language models, such as the recently introduced Model M, have provided significant gains over a range of tasks [1]. Training such models requires a l...
Abhinav Sethy, Stanley F. Chen, Bhuvana Ramabhadra...
Internet protocols encapsulate a significant amount of state, making implementing the host software complex. In this paper, we define the Statecall Policy Language (SPL) which pr...