1. What Limits Our Capacity to Process Nested Long-Range Dependencies in Sentence Comprehension?
- Author
-
Stanislas Dehaene, Jean-Rémi King, Yair Lakretz, Chaire Psychologie cognitive expérimentale, Collège de France (CdF (institution)), Laboratoire des systèmes perceptifs (LSP), Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL), Centre National de la Recherche Scientifique (CNRS), Facebook AI Research [Paris] (FAIR), Facebook, Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Collège de France - Chaire Psychologie cognitive expérimentale, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and ANR-17-EURE-0017,FrontCog,Frontières en cognition(2017)
- Subjects
Opinion ,Computer science ,media_common.quotation_subject ,General Physics and Astronomy ,lcsh:Astrophysics ,02 engineering and technology ,computer.software_genre ,Psycholinguistics ,Sentence processing ,03 medical and health sciences ,0302 clinical medicine ,lcsh:QB460-466 ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:Science ,ComputingMilieux_MISCELLANEOUS ,media_common ,Structure (mathematical logic) ,Parsing ,Grammar ,double center-embeddings ,business.industry ,sentence processing ,[SCCO.LING]Cognitive science/Linguistics ,lcsh:QC1-999 ,Comprehension ,language model ,lcsh:Q ,020201 artificial intelligence & image processing ,Artificial intelligence ,Language model ,business ,long-range dependencies ,artificial neural networks ,computer ,lcsh:Physics ,030217 neurology & neurosurgery ,Natural language processing ,Sentence - Abstract
International audience; Sentence comprehension requires inferring, from a sequence of words, the structure of syntactic relationships that bind these words into a semantic representation. Our limited ability to build some specific syntactic structures, such as nested center-embedded clauses (e.g., “The dog that the cat that the mouse bit chased ran away”), suggests a striking capacity limitation of sentence processing, and thus offers a window to understand how the human brain processes sentences. Here, we review the main hypotheses proposed in psycholinguistics to explain such capacity limitation. We then introduce an alternative approach, derived from our recent work on artificial neural networks optimized for language modeling, and predict that capacity limitation derives from the emergence of sparse and feature-specific syntactic units. Unlike psycholinguistic theories, our neural network-based framework provides precise capacity-limit predictions without making any a priori assumptions about the form of the grammar or parser. Finally, we discuss how our framework may clarify the mechanistic underpinning of language processing and its limitations in the human brain.
- Published
- 2020
- Full Text
- View/download PDF