We present a method of grounded word learning that is powerful enough to learn the meanings of first and second person pronouns. The model uses the understood words in an utteran...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segm...
Elizabeth Shriberg, Andreas Stolcke, Dilek Z. Hakk...
Abstract. This paper explores the possibility of using a modified Expectation-Maximization algorithm to estimate parameters for a simple hierarchical generative model for XML retr...
: Conventional hardware platforms are far from reaching real-time simulation requirements of complex spiking neural networks (SNN). Therefore we designed an accelerator board with ...