Distributed semantic representations for modeling human judgment
People make judgments about thousands of different objects and concepts on a day-to-day
basis; however, capturing the knowledge that subserves these judgments has been difficult …
basis; however, capturing the knowledge that subserves these judgments has been difficult …
From words-as-mappings to words-as-cues: The role of language in semantic knowledge
Semantic knowledge (or semantic memory) is knowledge we have about the world. For
example, we know that knives are typically sharp, made of metal, and that they are tools …
example, we know that knives are typically sharp, made of metal, and that they are tools …
Classifying phonological categories in imagined and articulated speech
This paper presents a new dataset combining 3 modalities (EEG, facial, and audio) during
imagined and vocalized phonemic and single-word prompts. We pre-process the EEG data …
imagined and vocalized phonemic and single-word prompts. We pre-process the EEG data …
Deep artificial neural networks reveal a distributed cortical network encoding propositional sentence-level meaning
Understanding how and where in the brain sentence-level meaning is constructed from
words presents a major scientific challenge. Recent advances have begun to explain brain …
words presents a major scientific challenge. Recent advances have begun to explain brain …
Predicting neural activity patterns associated with sentences using a neurobiologically motivated model of semantic representation
We introduce an approach that predicts neural representations of word meanings contained
in sentences then superposes these to predict neural representations of new sentences. A …
in sentences then superposes these to predict neural representations of new sentences. A …
Visually grounded and textual semantic models differentially decode brain activity associated with concrete and abstract nouns
Important advances have recently been made using computational semantic models to
decode brain activity patterns associated with concepts; however, this work has almost …
decode brain activity patterns associated with concepts; however, this work has almost …
An integrated neural decoder of linguistic and experiential meaning
The brain is thought to combine linguistic knowledge of words and nonlinguistic knowledge
of their referents to encode sentence meaning. However, functional neuroimaging studies …
of their referents to encode sentence meaning. However, functional neuroimaging studies …
[HTML][HTML] Interpretable semantic vectors from a joint model of brain-and text-based meaning
Vector space models (VSMs) represent word meanings as points in a high dimensional
space. VSMs are typically created using a large text corpora, and so represent word …
space. VSMs are typically created using a large text corpora, and so represent word …
Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text
Embodiment theory predicts that mental imagery of object words recruits neural circuits
involved in object perception. The degree of visual imagery present in routine thought and …
involved in object perception. The degree of visual imagery present in routine thought and …
Computer vision and natural language processing: recent approaches in multimedia and robotics
P Wiriyathammabhum, D Summers-Stay… - ACM Computing …, 2016 - dl.acm.org
Integrating computer vision and natural language processing is a novel interdisciplinary field
that has received a lot of attention recently. In this survey, we provide a comprehensive …
that has received a lot of attention recently. In this survey, we provide a comprehensive …