This paper describes an algorithm for spoken language acquisition through a human-robot interface based on speech, vision, and behavior. In this algorithm the grounded language knowledge is represented by graphical statistical models consisting of hidden Markov models and stochastic context-free grammar. The learning of the lexicon is based on the independence between speech and visual features...

The aim of the article is to examine the Academic Model United Nations (Model UN) as a context-based integrative educational technique in profession-oriented foreign language teaching (FLT); to point out the context-based integrative nature of profession-oriented language learning and highlight the importance of using product-based educational techniques in FLT for developing students’ future p...

several semantic image search schemes have been recently proposed to retrieve images from the web. however, the query context is regularly ignored in these techniques and hence, many of the returned images are not adequately relevant. in this paper, we make use of context to further confine the outcome of the semantic search engines. for this purpose, we propose a hybrid search engine which uti...

Currently, gene finding and RNA secondary structure prediction are performed separately. This is only valid if, for any DNA sequence the location of genes and corresponding RNA secondary structure can assumed to be independent. I develop methods that take a hidden Markov model for gene finding and a stochastic context-free grammar for RNA secondary structure prediction and from these, construct...

Currently, gene finding and RNA secondary structure prediction are performed separately. This is only valid if, for any DNA sequence the location of genes and corresponding RNA secondary structure can assumed to be independent. I develop methods that take a hidden Markov model for gene finding and a stochastic context-free grammar for RNA secondary structure prediction and from these, construct...

We propose a new method for semantic parsing of ambiguous and ungrammatical input, such as search queries. We do so by building on an existing semantic parsing framework that uses synchronous context free grammars (SCFG) to jointly model the input sentence and output meaning representation. We generalize this SCFG framework to allow not one, but multiple outputs. Using this formalism, we constr...

Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context information and adapting systems behavior accordingly. Several context models have been defined and various context-aware middleware has been developed in order to simplify the development of context-aware applications. Unfortunately, the development of an application by usin...

In this paper, we compare three different approaches to build a probabilistic context-free grammar for natural language parsing from a tree bank corpus: (1) a model that simply extracts the rules contained in the corpus and counts the number of occurrences of each rule; (2) a model that also stores information about the parent node’s category, and (3) a model that estimates the probabilities ac...