We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
This paper proposes a new approach to the challenging open-set language detection task. Most state-of-the-art approaches make use of data sources with several out-of-set languages...
Mohamed Faouzi BenZeghiba, Jean-Luc Gauvain, Lori ...
One commonly used approach for language recognition is to convert the input speech into a sequence of tokens such as words or phones and then to use these token sequences to deter...
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...
In this paper, we present a set of optimizations for a spoken language interface for mobile devices that can improve the recognition accuracy and user interaction experience. A com...