Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms

The effects of lexical context on phonological processing are pervasive and there have been indications that such effects may be modulated by attention. However, attentional modulation in speech processing is neither well-documented nor well-understood. Experiment 1 demonstrated attentional modulation of lexical facilitation of speech sound recognition when task and critical stimuli were identical across attention conditions. We propose modulation of lexical activation as a neurophysiologically-plausible computational mechanism that can account for this type of modulation. Contrary to the claims of critics, this mechanism can account for attentional modulation without violating the principle of interactive processing. Simulations of the interactive TRACE model extended to include two different ways of modulating lexical activation showed that each can account for attentional modulation of lexical feedback effects. Experiment 2 tested conflicting predictions from the two implementations and provided evidence that is consistent with bias input as the mechanism of attentional control of lexical activation.

[1]  Matthew M Botvinick,et al.  Short-term memory for serial order: a recurrent neural network model. , 2006, Psychological review.

[2]  Prahlad Gupta,et al.  Does neighborhood density influence repetition latency for nonwords? Separating the effects of density and duration , 2004 .

[3]  Heike Martensen,et al.  The lexical bias effect is modulated by context, but the standard monitoring account doesn’t fly: Related beply to Baars et al. (1975) ☆ , 2005 .

[4]  M. Turvey,et al.  Initial phonemes are detected faster in spoken words than in spoken nonwords , 1976 .

[5]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .

[6]  A. Treisman,et al.  Voluntary Attention Modulates fMRI Activity in Human MT–MST , 1997, Neuron.

[7]  G. Miller,et al.  Cognitive science. , 1981, Science.

[8]  W. Ganong Phonetic categorization in auditory word perception. , 1980, Journal of experimental psychology. Human perception and performance.

[9]  Arthur G. Samuel,et al.  Lexical inhibition and attentional allocation during speech perception: Evidence from phoneme monitoring , 1997 .

[10]  Lori L. Holt,et al.  Are there interactive processes in speech perception? , 2006, Trends in Cognitive Sciences.

[11]  P. Luce,et al.  Phonotactics, density, and entropy in spoken word recognition , 2001 .

[12]  A G Samuel,et al.  An empirical and meta-analytic evaluation of the phoneme identification task. , 1993, Journal of experimental psychology. Human perception and performance.

[13]  Colin M. Macleod,et al.  Interdimensional interference in the Stroop effect: uncovering the cognitive and neural anatomy of attention , 2000, Trends in Cognitive Sciences.

[14]  Anne Cutler,et al.  Phoneme identification and the lexicon , 1987, Cognitive Psychology.

[15]  D Norris,et al.  Merging information in speech recognition: Feedback is never necessary , 2000, Behavioral and Brain Sciences.

[16]  L. Pylkkänen,et al.  Tracking the time course of word recognition with MEG , 2003, Trends in Cognitive Sciences.

[17]  R. Desimone,et al.  Selective attention gates visual processing in the extrastriate cortex. , 1985, Science.

[18]  James L. McClelland,et al.  Understanding normal and impaired word reading: computational principles in quasi-regular domains. , 1996, Psychological review.

[19]  P. Luce,et al.  Probabilistic Phonotactics and Neighborhood Activation in Spoken Word Recognition , 1999 .

[20]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[21]  James L. McClelland,et al.  Computational and behavioral investigations of lexically induced delays in phoneme recognition , 2005 .

[22]  James L. McClelland,et al.  On the control of automatic processes: a parallel distributed processing account of the Stroop effect. , 1990, Psychological review.

[23]  Jeffrey L. Elman,et al.  Finding Structure in Time , 1990, Cogn. Sci..

[24]  Michael S Vitevitch,et al.  The influence of sublexical and lexical representations on the processing of spoken words in English , 2003, Clinical linguistics & phonetics.

[25]  R. Duncan Luce,et al.  Individual Choice Behavior , 1959 .

[26]  R. Salmelin,et al.  Time course of top-down and bottom-up influences on syllable processing in the auditory cortex. , 2006, Cerebral cortex.

[27]  J D Cohen,et al.  A network model of catecholamine effects: gain, signal-to-noise ratio, and behavior. , 1990, Science.

[28]  Elizabeth Jefferies,et al.  Lexical and semantic binding in verbal short-term memory , 2006 .

[29]  David C. Plaut,et al.  Strategic Control Over Rate of Processing in Word Reading: A Computational Investigation of the Tempo-Naming Task , 2000 .

[30]  James L. McClelland,et al.  The TRACE model of speech perception , 1986, Cognitive Psychology.

[31]  S. Monsell,et al.  Lexical and sublexical translation of spelling to sound : Strategic anticipation of lexical status , 1992 .

[32]  Peter D. Eimas,et al.  Attention and the role of dual codes in phoneme monitoring , 1990 .