A popular tradition of studying semantic representation has been driven by the assumption that word meaning can be learned from the linguistic environment, despite ample evidence suggesting that language is grounded in ...

Previous research has shown that rhythmic training enhances phonological speech processing (e.g., [1, 2, 3, 4]). Yet little is known about whether rhythmic training can also help to improve pronunciation in a second language ...

There is an increasing consensus to regard gesture and speech as parts of an integrated communication system, in part because of the findings related to their temporal coordination at different levels. In general, results ...

Recent state-of-the-art neural language models share the representations of words given by the input and output mappings. We propose a simple modification to these architectures that decouples the hidden state from the ...

Zero-shot methods in language, vision and other domains rely on a cross-space mapping function that projects vectors from the relevant feature space (e.g., visualfeature-based image representations) to a large semantic ...

La irrupción de la inteligencia artificial en los medios de comunicación está generando un intenso debate en torno a sus capacidades y repercusiones. Se percibe como una posibilidad o una amenaza según se valore su ...

The following work describes a method to automatically classify the sense selection of the complex type Location/Organization –which depends on regular polysemy– using shallow features, as well as a way to increase the ...

Distributional semantics has very successfully modeled semantic phenomena at the word level, and recently interest has grown in extending it to capture the meaning of phrases via semantic composition. We present experiments ...

As deep networks begin to be deployed as autonomous agents, the issue of how they can communicate with each other becomes important. Here, we train two deep nets from scratch to perform large-scale referent identification ...