Information distillation techniques are used to analyze and interpret large volumes of speech and text archives in multiple languages and produce structured information of interes...
In this work we implement a confidence estimation system based on a Naive Bayes classifier, by using the maximum entropy paradigm. The model takes information from various sourc...
Automatic Speech Recognition (ASR) systems continue to make errors during search when handling various phenomena including noise, pronunciation variation, and out of vocabulary (O...
Christopher M. White, Geoffrey Zweig, Lukas Burget...
A new method for hiding digital data in the bitstream of an ACELP speech codec is proposed in this paper. The key element of our method is an alternative search strategy for the A...
This paper extends language identification (LID) techniques to a large scale accent classification task: 23-way classification of foreign-accented English. We find that a pure...
Ghinwa F. Choueiter, Geoffrey Zweig, Patrick Nguye...
In this paper we describe the application of a feature-space transform based on constrained maximum likelihood linear regression for unsupervised compensation of channel and speak...
Recently, we proposed a model for the steady-state estimation error of real-valued constant-modulus-based algorithms as a function of the a priori error and of a term that measure...
We describe our early experience building and optimizing GOOG-411, a fully automated, voice-enabled, business finder. We show how taking an iterative approach to system developme...
SensorScope is a collaborative project between network, signal processing, and environmental researchers that aims at providing a cheap and out-of-the-box environmental monitoring...