This study demonstrates that listeners use lexical knowledge in perceptual learning of speech sounds. Dutch listeners first made lexical decisions on Dutch words and nonwords. The final fricative of 20 critical words had been replaced by an ambiguous sound, between [f] and [s]. One group of listeners heard ambiguous [f]-final words (e.g., [WItlo?], from witlof, chicory) and unambiguous [s]-final words (e.g., naaldbos, pine forest). Another group heard the reverse (e.g., ambiguous [na:ldbo?], unambiguous witlof). Listeners who had heard [?] in [f]-final words were subsequently more likely to categorize ambiguous sounds on an [f]-[s] continuum as [f] than those who heard [?] in [s]-final words. Control conditions ruled out alternative explanations based on selective adaptation and contrast. Lexical information can thus be used to train categorization of speech. This use of lexical information differs from the on-line lexical feedback embodied in interactive models of speech perception. In contrast to on-line feedback, lexical feedback for learning is of benefit to spoken word recognition (e.g., in adapting to a newly encountered dialect).

IntroductionPsychological processing involves converting information from one form to another. In speech recognition -the focus of this target article -sounds uttered by a speaker are converted to a sequence of words recognized by a listener. The logic of the process requires information to flow in one direction: from sounds to words. This direction of information flow is unavoidable and necessary for a speech recognition model to function.Our target article addresses the question of whether output from word recognition is fed back to earlier stages of processing, such as acoustic or phonemic analysis. Such feedback entails information flow in the opposite direction -from words to sounds. Information flow from word processing to these earlier stages is not required by the logic of speech recognition and cannot replace the necessary flow of information from sounds to words. Thus it could only be included in models of speech recognition as an additional component.The principle of Occam's razor instructs theorists never to multiply entities unnecessarily. Applied to the design of processing models, this constraint excludes any feature that BEHAVIORAL AND BRAIN SCIENCES (2000) 23, Abstract: 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.Keywords: computational modeling; feedback; lexical processing; modularity; phonemic decisions; reading; speech recognition; word recognitionDennis Norris is a member of the senior scientific staff of the Medical Research Council Cognition and Brain Sciences Unit, Cambridge, United Kingdom. James McQueen is a member of the scientific staff of the Max-Planck-Institute for Psycholinguistics, Nijmegen, The Netherlands. Anne Cutler is director (language comprehension) of the Max-Planck-Institute for Psycholinguistics and professor of comparative psycholinguistics at the U...

A Bayesian model of continuous speech recognition is presented. It is based on Shortlist (D. Norris, 1994; D. Norris, J. M. McQueen, A. Cutler, & S. Butterfield, 1997) and shares many of its key assumptions: parallel competitive evaluation of multiple lexical hypotheses, phonologically abstract prelexical and lexical representations, a feedforward architecture with no online feedback, and a lexical segmentation algorithm based on the viability of chunks of the input as possible words. Shortlist B is radically different from its predecessor in two respects. First, whereas Shortlist was a connectionist model based on interactive-activation principles, Shortlist B is based on Bayesian principles. Second, the input to Shortlist B is no longer a sequence of discrete phonemes; it is a sequence of multiple phoneme probabilities over 3 time slices per segment, derived from the performance of listeners in a large-scale gating study. Simulations are presented showing that the model can account for key findings: data on the segmentation of continuous speech, word frequency effects, the effects of mispronunciations on word recognition, and evidence on lexical involvement in phonemic decision making. The success of Shortlist B suggests that listeners make optimal Bayesian decisions during spoken-word recognition.

Experiments 1 and 2 examined the time-course of retrieval of phonological, visual-shape and semantic knowledge as Dutch participants listened to sentences and looked at displays of four pictures. Given a sentence with beker, `beaker', for example, the display contained phonological (a beaver, bever), shape (a bobbin, klos), and semantic (a fork, vork) competitors. When the display appeared at sentence onset, fixations to phonological competitors preceded fixations to shape and semantic competitors. When display onset was 200 ms before (e.g.) beker, fixations were directed to shape and then semantic competitors, but not phonological competitors. In Experiments 3 and 4, displays contained the printed names of the previously-pictured entities; only phonological competitors were fixated preferentially. These findings suggest that retrieval of phonological, shape and semantic knowledge in the spoken-word and picture-recognition systems is cascaded, and that visual attention shifts are co-determined by the time-course of retrieval of all three knowledge types and by the nature of the information in the visual environment