We describe an account of lexically guided tuning of speech perception based on interactive processing and Hebbian learning. Interactive feedback provides lexical information to prelexical levels, and Hebbian learning uses that information to retune the mapping from auditory input to prelexical representations of speech. Simulations of an extension of the TRACE model of speech perception are presented that demonstrate the efficacy of this mechanism. Further simulations show that acoustic similarity can account for the patterns of speaker generalization. This account addresses the role of lexical information in guiding both perception and learning with a single set of principles of information propagation.

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.

A number of studies suggest that attention can modulate the extent to which lexical processing influences phonological processing. We propose dampening of activation as a neurophysiologically-plausible computational mechanism that can account for this type of modulation in the context of an interactive model of speech perception. Simulation results from two concrete implementations of this mechanism indicate that each of the implementations can account for attentional modulation of lexical feedback effects but that they have different consequences on the dynamics of lexical activation. We also present a behavioral test of attentional modulation of lexical effects that is not contaminated by task or stimulus effects.

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.

This study investigates speech comprehension in competing multi-talker babble. We examined the effects of number of simultaneous talkers and of frequency of words in the babble on lexical decision to target words. Results revealed better performance at a low talker number (n = 2). Importantly, frequency of words in the babble significantly affected performance: high frequency word babble interfered more strongly with word recognition than low frequency babble. This informational masking was particularly salient for the 2-talker babble. These findings suggest that investigating speech-in-speech comprehension may provide crucial information on lexical competition processes that occur in real-time during word recognition. Index Terms: speech-in-noise, informational masking, lexical competition