Visual statistical learning in infancy: evidence for a domain general learning mechanism

Kirkham, Natasha Z.; Slemmer, Jonathan A.; Johnson, Scott P.

doi:10.1016/s0010-0277(02)00004-5

Cited by 922 publications

(806 citation statements)

References 14 publications

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“…First, the perceptual advances of the first year of life -e.g., progressive sensitivization to prosodic coherence in ever smaller units of input speech from 4 to 11 months (clauses, phrases, words: for a review, see Jusczyk, 1997); the limiting of consonant discrimination to phonological contrasts supported by the ambient language by 10-12 months (Werker & Tees, 1981); and growth in familiarity with the specific characteristics of ambient language prosodic and phonotactic patterning in the period 9 to 12 months (e.g., Jusczyk et al, 1993;Jusczyk et al, 1994) -are well documented. This profile of perceptual accommodation to the ambient language appears to reflect implicit learning of the distributional patterning of input speech, a kind of automatic "statistical" or "distributional" learning that has been convincingly demonstrated experimentally in studies of infant responses to briefly experienced nonword sequences (Saffran et al, 1996;Johnson & Jusczyk, 2001) as well as to non-linguistic regularities (Kirkham et al, 2002).…”

Section: The Sources Of Phonological Knowledgementioning

confidence: 72%

The sources of phonological knowledge: a cross-linguistic perspective

Vihman¹,

Kunnari²

2006

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Section: The Sources Of Phonological Knowledgementioning

confidence: 72%

The sources of phonological knowledge: a cross-linguistic perspective

Vihman¹,

Kunnari²

2006

rlv

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“…At their best, artificial language studies can be highly informative about the fundamental mechanisms of learning that are continuous across development and even across species. Work on statistical segmentation and grouping has exemplified this description (Saffran et al, 1996b(Saffran et al, , 1996aAslin, Saffran, & Newport, 1998;Hauser, Newport, & Aslin, 2001;Kirkham, Slemmer, & Johnson, 2002;Fiser & Aslin, 2002). Although it is not always clear how this work connects with particular tasks in language acquisition, the identification and characterization of basic learning mechanisms is in itself an important task.…”

Section: Discussionmentioning

confidence: 99%

Overcoming Memory Limitations in Rule Learning

Frank¹,

Gibson

2011

Language Learning and Development

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Adults, infants, and other species are able to learn and generalize abstract patterns from sequentially-presented stimuli. Rule learning of this type may be involved in children's acquisition of linguistic structure, but the nature of the mechanisms underlying these abilities is unknown. While inferences regarding the capabilities of these mechanisms are commonly made based on the pattern of successes and failures in simple artificial-language rule-learning tasks, failures may be driven by memory limitations rather than intrinsic limitations on the kinds of computations that learners can perform. Here we show that alleviating memory constraints on adult learners through concurrent visual presentation of stimuli allowed them to succeed in learning regularities in three difficult artificial rule-learning experiments where participants had previously failed to learn via sequential auditory presentation. These results suggest that memory constraints, rather than intrinsic limitations on learning, may be a parsimonious explanation for many previously reported failures. We argue that future work should attempt to characterize the role of memory constraints in natural and artificial language learning.

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“…Fodor, 1983Fodor, , 2000. Indeed, both segmentation cues are available throughout linguistic development (i.e., since an early age-e.g., Johnson & Jusczyk, 2001;Kirkham, Slemmer & Johnson, 2002;-and in adulthood-e.g., Mattys, 2004, but only coarticulation is speech-specific, and hence may be processed by an encapsulated system that may operate quite independently of attention resources. On the contrary, TP computation relies on a domain-general learning mechanism (e.g., Fiser & Aslin, 2001;Perruchet & Pacton, 2006;Turk-Browne et al, 2005) that may be more sensitive to attention resources and hence to cognitive load.…”

Section: General R R Discussionmentioning

confidence: 99%

The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

Fernandes

Kolinsky

Ventura

2010

Attention, Perception, & Psychophysics

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MaterialAL material. To achieve realistic coarticulation, we used naturally produced utterances rather than synthesized speech, and created concatenated and coarticulated versions of the AL stimuli (for the detailed method, see Fernandes et al., 2007). On the basis of Fernandes et al.'s pretests, we already know that the use of naturally produced rather than synthesized utterances does have an impact on ALL performance.All the natural speech stimuli were recorded in a soundproof room (using WaveLab Lite Program, version 2.52) by a European Portuguese female native speaker using a Shure M58 microphone and sampled at a rate of 22.05 kHz with 16-bit conversion. Adobe Audition 1.5 and Praat 4.2.24 (available at http://fon.hum.uva.nl/ praat/) were used for editing of the digitized versions of the stimuli (i.e., syllables, words, and part-words). These stimuli were closely matched to a synthesized stream in all relevant acoustic parameters, such as speaking rate (approximately 270 syllables per minute), AL stimuli duration, lack of lexical stress cues to word boundaries, and pitch contour (through flattening to monotone 220 Hz).The AL used by Fernandes et al. (2007) was adopted here. It was constituted by six trisyllabic AL words (i.e., / /, / /, / /, / /, / /, / /). TPs between adjacent syllables were always higher within than between AL words. Half of the AL words had higher TPs (high-TP words, ranging from .75 to 1) than the other half (low-TP words, ranging from .50 to .58), but all occurred with the same frequency in the AL stream.

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Visual statistical learning in infancy: evidence for a domain general learning mechanism

Cited by 922 publications

References 14 publications

The sources of phonological knowledge: a cross-linguistic perspective

The sources of phonological knowledge: a cross-linguistic perspective

Overcoming Memory Limitations in Rule Learning

The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues

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