David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Behavioral and Brain Sciences 23 (3):299-325 (2000)
Top-down feedback does not benefit speech recognition; on the contrary, it can hinder it. No experimental data imply that feedback loops are required for speech recognition. Feedback is accordingly unnecessary and spoken word recognition is modular. To defend this thesis, we analyse lexical involvement in phonemic decision making. TRACE (McClelland & Elman 1986), a model with feedback from the lexicon to prelexical processes, is unable to account for all the available data on phonemic decision making. The modular Race model (Cutler & Norris 1979) is likewise challenged by some recent results, however. We therefore present a new modular model of phonemic decision making, the Merge model. In Merge, information flows from prelexical processes to the lexicon without feedback. Because phonemic decisions are based on the merging of prelexical and lexical information, Merge correctly predicts lexical involvement in phonemic decisions in both words and nonwords. Computer simulations show how Merge is able to account for the data through a process of competition between lexical hypotheses. We discuss the issue of feedback in other areas of language processing and conclude that modular models are particularly well suited to the problems and constraints of speech recognition. Key Words: computational modeling; feedback; lexical processing; modularity; phonemic decisions; reading; speech recognition; word recognition.
|Keywords||computational modeling feedback lexical processing modularity phonemic decisions reading speech recognition word recognition|
|Categories||categorize this paper)|
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Citations of this work BETA
Matthew K. Leonard & Edward F. Chang (forthcoming). Dynamic Speech Representations in the Human Temporal Lobe. Trends in Cognitive Sciences.
David W. Gow & Jennifer A. Segawa (2009). Articulatory Mediation of Speech Perception: A Causal Analysis of Multi-Modal Imaging Data. Cognition 110 (2):222-236.
James M. McQueen, Anne Cutler & Dennis Norris (2006). Phonological Abstraction in the Mental Lexicon. Cognitive Science 30 (6):1113-1126.
Manuel Carreiras, Blair C. Armstrong, Manuel Perea & Ram Frost (2014). The What, When, Where, and How of Visual Word Recognition. Trends in Cognitive Sciences 18 (2):90-98.
Odette Scharenborg, Dennis Norris, Louis Bosch & James M. McQueen (2005). How Should a Speech Recognizer Work? Cognitive Science 29 (6):867-918.
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