This paper presents a new connectionist model of the grounding of linguistic quantifiers in perception that takes into consideration the contextual factors affecting the use of vague quantifiers. A preliminary validation of the model is presented through the training and testing of the model with experimental data on the rating of quantifiers. The model is able to perform the “psychological” counting of objects (fish) in visual scenes and to select the quantifier that best describes the scene, as in psychological experiments
This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for...
In this paper, we investigate whether a neural network model can learn the meaning of natural langua...
International audienceThis book introduces a host of connectionist models of cognition and behavior....
Abstract. This paper presents a new connectionist model of the grounding of linguistic quantifiers i...
This thesis presents experimental and computational modeling studies on the mental representations o...
This thesis presents experimental and computational modeling studies on the mental representations o...
Defining the meaning of vague quantifiers (‘few’, ‘most’, ‘all’) has been, and still is, the Holy Gr...
We examine the verification of simple quantifiers in natural language from a computational model per...
Connectionist modeling (AKA neural network modeling, connectionism) is rapidly becoming a dominant d...
Traditional approaches to language processing have been based on explicit, discrete representations ...
This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for ...
If we want to explain cognitive processes with means of connectionist networks, these networks have ...
The literature on vague quantifiers in English (words like “some”, “many”, etc.) is replete with dem...
Traditional approaches to language processing have been based on explicit, discrete representations ...
This paper is concerned with constraints on learning quantifiers, particularly those cognitive on hu...
This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for...
In this paper, we investigate whether a neural network model can learn the meaning of natural langua...
International audienceThis book introduces a host of connectionist models of cognition and behavior....
Abstract. This paper presents a new connectionist model of the grounding of linguistic quantifiers i...
This thesis presents experimental and computational modeling studies on the mental representations o...
This thesis presents experimental and computational modeling studies on the mental representations o...
Defining the meaning of vague quantifiers (‘few’, ‘most’, ‘all’) has been, and still is, the Holy Gr...
We examine the verification of simple quantifiers in natural language from a computational model per...
Connectionist modeling (AKA neural network modeling, connectionism) is rapidly becoming a dominant d...
Traditional approaches to language processing have been based on explicit, discrete representations ...
This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for ...
If we want to explain cognitive processes with means of connectionist networks, these networks have ...
The literature on vague quantifiers in English (words like “some”, “many”, etc.) is replete with dem...
Traditional approaches to language processing have been based on explicit, discrete representations ...
This paper is concerned with constraints on learning quantifiers, particularly those cognitive on hu...
This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for...
In this paper, we investigate whether a neural network model can learn the meaning of natural langua...
International audienceThis book introduces a host of connectionist models of cognition and behavior....