Categorizing words using 'frequent frames': what cross-linguistic analyses reveal about distributional acquisition strategies.
Mintz (2003) described a distributional environment called a frame, defined as the co-occurrence of two context words with one intervening target word. Analyses of English child-directed speech showed that words that fell within any frequently occurring frame consistently belonged to the same grammatical category (e.g. noun, verb, adjective, etc.). In this paper, we first generalize this result to French, a language in which the function word system allows patterns that are potentially detrimental to a frame-based analysis procedure. Second, we show that the discontinuity of the chosen environments (i.e. the fact that target words are framed by the context words) is crucial for the mechanism to be efficient. This property might be relevant for any computational approach to grammatical categorization. Finally, we investigate a recursive application of the procedure and observe that the categorization is paradoxically worse when context elements are categories rather than actual lexical items. Item-specificity is thus also a core computational principle for this type of algorithm. Our analysis, along with results from behavioural studies (Gómez, 2002; Gómez and Maye, 2005; Mintz, 2006), provides strong support for frames as a basis for the acquisition of grammatical categories by infants. Discontinuity and item-specificity appear to be crucial features.
Laboratoire de Sciences Cognitives et Psycholinguistique, DEC-ENS/EHESS, CNRS, Paris, France. emmanuel.chemla@ens.fr
Emmanuel
E
Chemla
Toben H
TH
Mintz
Savita
S
Bernal
Anne
A
Christophe
D000465:Algorithms; D002965:Classification; D006801:Humans; D007802:Language; D008960:Models, Psychological; D016008:Statistical Distributions; D014825:Vocabulary