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Two artificial-language learning experiments directly compared English, French, and Dutch listeners' use of suprasegmental cues for continuous-speech segmentation. In both experiments, listeners heard unbroken sequences of consonant-vowel syllables, composed of recurring three-and four-syllable "words." These words were demarcated by ͑a͒ no cue other than transitional probabilities induced by their recurrence, ͑b͒ a consistent left-edge cue, or ͑c͒ a consistent right-edge cue. Experiment 1 examined a vowel lengthening cue. All three listener groups benefited from this cue in right-edge position; none benefited from it in left-edge position. Experiment 2 examined a pitch-movement cue. English listeners used this cue in left-edge position, French listeners used it in right-edge position, and Dutch listeners used it in both positions. These findings are interpreted as evidence of both language-universal and language-specific effects. Final lengthening is a language-universal effect expressing a more general ͑non-linguistic͒ mechanism. Pitch movement expresses prominence which has characteristically different placements across languages: typically at right edges in French, but at left edges in English and Dutch. Finally, stress realization in English versus Dutch encourages greater attention to suprasegmental variation by Dutch than by English listeners, allowing Dutch listeners to benefit from an informative pitch-movement cue even in an uncharacteristic position.

Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants' ability to track transitional probabilities between syllables in an artificial language can scale up to the challenge of natural language. We do so by testing both 5.5-and 8-month-olds' ability to segment an artificial language containing four words of uniform length (all CVCV) or four words of varying length (two CVCV, two CVCVCV). The transitional probability cues to word boundaries were held equal across the two languages. Both age groups segmented the language containing words of uniform length, demonstrating that even 5.5-montholds are extremely sensitive to the conditional probabilities in their environment. However, neither age group succeeded in segmenting the language containing words of varying length, despite the fact that the transitional probability cues defining word boundaries were equally strong in the two languages. We conclude that infants' statistical learning abilities may not be as robust as earlier studies have suggested.

Speech production research has demonstrated that the first language (L1) often interferes with production in bilinguals’ second language (L2), but it has been suggested that bilinguals who are L2-dominant are the most likely to suppress this L1-interference. While prolonged contextual changes in bilinguals’ language use (e.g., stays overseas) are known to result in L1 and L2 phonetic shifts, code-switching provides the unique opportunity of observing the immediate phonetic effects of L1-L2 interaction. We measured the voice onset times (VOTs) of Greek–English bilinguals’ productions of /b, d, p, t/ in initial and medial contexts, first in either a Greek or English unilingual mode, and in a later session when they produced the same target pseudowords as a code-switch from the opposing language. Compared to a unilingual mode, all English stops produced as code-switches from Greek, regardless of context, had more Greek-like VOTs. In contrast, Greek stops showed no shift toward English VOTs, with the exception of medial voiced stops. Under the specifically interlanguage condition of code-switching we have demonstrated a pervasive influence of the L1 even in L2-dominant individuals.

Is it possible to learn the relation between 2 nonadjacent events? M. Peña, L. L. Bonatti, M. Nespor, and J. Mehler (2002) claimed this to be possible, but only in conditions suggesting the involvement of algebraic-like computations. The present article reports simulation studies and experimental data showing that the observations on which Peña et al. grounded their reasoning were flawed by deep methodological inadequacies. When the invalid data are set aside, the available evidence fits exactly with the predictions of a theory relying on ubiquitous associative mechanisms. Because nonadjacent dependencies are frequent in natural language, this reappraisal has far-reaching implications for the current debate on the need for rule-based computations in human adaptation to complex structures.The idea that most higher cognitive activities, especially language comprehension and production, are based on abstract, rulebased operations on symbolic contents is one of the cornerstones of the mainstream tradition in cognitive psychology. However, over the last 2 decades or so, an alternative view has gained increasing influence. This alternative conception is rooted in the traditional associative view of mind, but its recent upsurge is essentially related to the growth of connectionist modeling (e.g., McClelland & Rumelhart, 1986). Indeed, connectionist studies have shown that certain activities that were once thought of as straightforward evidence for rule-based computations can be simulated by models that rely only on associative mechanisms. This issue has crystallized around two broad conceptions of the mind, often thought of today as an opposition between those who advocate the need for assuming algebraic-like computations (e.g., Marcus, Vijayan, Rao, & Vishton, 1999;Pinker, 1997) and the proponents of statistical/distributional approaches (e.g., Seidenberg & MacDonald, 1999). The English past tense has been a focus for this debate from its outset, and the number of papers pertaining to this issue over the last few years (e.g., Pinker & Ullman, 2002;Ramscar, 2002) suggests that it is still unsettled despite a considerable amount of research effort.A newcomer in this lively debate is the learning of nonadjacent (or remote) dependencies. The major part of the traditional literature on associative learning has dealt with relations between adjacent events. This is true both for the domain of animal conditioning and for studies on paired-associate learning in humans. In both cases, the items to be associated are displayed in close temporal or spatial proximity. The same is true for the more recent studies on implicit learning (e.g. Stadler & Frensch, 1998). Looking at a standard flowchart of a finite-state grammar commonly used in artificial grammar studies is sufficient to show that relations are built between contiguous elements. 1 Several studies have shown that those adjacent relations were far more relevant for linguistic structure than researchers had claimed in the past. For instance, Redington, Chater, and Finch (199...