Unsupervised learning of linguistic structure is a difficult problem. A common approach is to define a generative model and maximize the probability of the hidden structure give...
One of the issues of Artificial Intelligence is the transfer of the knowledge conveyed by Natural Language into formalisms that a computer can interpret. In the Natural Language P...
Space is a spatial programming language designed to exploit the massive parallelism available in a formal model of computation called the Synchronic A-Ram, and physically related ...
We present an implemented model for speech recognition in natural environments which relies on contextual information about salient entities to prime utterance recognition. The hyp...
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...