In a series of 5 experiments, we investigated whether the processing of phonologically assimilated utterances is influenced by language learning. Previous experiments had shown that phonological assimilations, such as /lean#bacon/→ [leam bacon], are compensated for in perception. In this article, we investigated whether compensation for assimilation can occur without experience with an assimilation rule using automatic event-related potentials. Our first experiment indicated that Dutch listeners compensate for a Hungarian assimilation rule. Two subsequent experiments, however, failed to show compensation for assimilation (...) by both Dutch and Hungarian listeners. Two additional experiments showed that this was due to the acoustic properties of the assimilated utterance, confirming earlier reports that phonetic detail is important in compensation for assimilation. Our data indicate that compensation for assimilation can occur without experience with an assimilation rule, in line with phonetic-phonological theories that assume that speech production is influenced by speech-perception abilities. (shrink)

One of the things you learn if you read books and articles in (or about) cognitive science is that the brain does a lot of "filling in"--not filling in, but "filling in"--in scare quotes. My claim today will be that this way of talking is not a safe bit of shorthand, or an innocent bit of temporizing, but a source of deep confusion and error. The phenomena described in terms of "filling in" are real, surprising, and theoretically important, but it (...) is a mistake to conceive of them as instances of something being filled in, for that vivid phrase always suggests too much--sometimes a little too much, but often a lot too much. Here are some examples (my boldface throughout). (shrink)

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. (shrink)