This paper addresses selecting between candidate pronunciations for out-of-vocabulary words in speech processing tasks. We introduce a simple, unsupervised method that outperforms...
Christopher M. White, Abhinav Sethy, Bhuvana Ramab...
The paper describes initial results in an ongoing project aimed at providing and analyzing standardized, representative data sets for typical context recognition tasks. Such data ...
Ernst A. Heinz, Kai S. Kunze, Stefan Sulistyo, Hol...
In this paper, we report on an empirical exploration of digital ink and speech usage in lecture presentation. We studied the video archives of five Master’s level Computer Scien...
Richard J. Anderson, Crystal Hoyer, Craig Prince, ...
We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-be...
Abstract--In a distributed speech recognition (DSR) framework, the speech features are quantized and compressed at the client and recognized at the server. However, recognition acc...