Similarity in the generalization of implicitly learned sound patterns

Cristià, Alejandrina; Mielke, Jeff; Daland, Robert; Peperkamp, Sharon

doi:10.1515/lp-2013-0010

Cited by 23 publications

(34 citation statements)

References 42 publications

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“…Our finding that participants generalized to new sounds is in line with the results of several other studies (Cristia et al, 2013;Finley & Badecker, 2009;Finley, 2011;Gallagher, 2013). However, those studies tested participants after extensive exposure to the language: 160 words (Cristia et al, 2013), 212 words (Gallagher, 2013) or 120 words (Finley & Badecker, 2009;Finley, 2011).…”

Section: Previous Studies Of Phonotactic Generalizationsupporting

confidence: 92%

“…Yet the same results may be consistent with a view in which participants evaluate the similarity between the consonant pattern of the test word and their memories of the consonant patterns in the exposure words (Goldinger, 1998;Nosofsky, 1986;Redington & Chater, 1996). Such a similarity metric would need to operate over phonological features rather than pure acoustic similarity (Cristia et al, 2013); to account for the results of Experiment 2a, that similarity metric would also need to make reference to the abstract notion of repetition, to prevent [s, s] from being considered more similar to [s, t] than to [t, t]. Once the representational apparatus is equated between the probabilistic abstraction model and the similarity-based exemplar models, however, the two classes of accounts become difficult to distinguish empirically (Barsalou, 1990;Hahn & Chater, 1998); indeed, exemplar models have been interpreted as a process-level implementation of the probabilistic abstraction approach (Shi et al, 2010).…”

Section: Mechanisms Of Generalizationsupporting

confidence: 68%

“…In these experiments, participants are presented with individual words in a miniature artificial language, and are then tested on novel words to determine what knowledge they have extracted from the language. Adult participants have shown evidence of learning the phonotactics of artificial languages in such diverse tasks as acceptability judgments (Richtsmeier, 2011), speech error patterns in production (Gaskell et al, 2014;Warker & Dell, 2006) and familiarity judgments (Cristia et al, 2013). Related findings have been reported in artificial language studies of morphological alternations (Finley & Badecker, 2009;Peperkamp et al, 2006;Wilson, 2003).…”

Section: Introductionmentioning

confidence: 56%

“…Similar findings have been reported for infants, who are typically tested using the headturn preference paradigm (Chambers et al, 2003;Cristià & Seidl, 2008;Saffran & Thiessen, 2003;Seidl & Buckley, 2005;Cristia & Peperkamp, 2012). Most importantly for the present study, multiple artificial language learning experiments have reported generalization beyond attested sounds (Cristia & Peperkamp, 2012;Cristia et al, 2013;Gallagher, 2013;Finley & Badecker, 2009;Marcus et al, 1999), though some studies have failed to find this effect (Peperkamp et al, 2006;Peperkamp & Dupoux, 2007).…”

Section: Introductionmentioning

confidence: 62%

“…However, those studies tested participants after extensive exposure to the language: 160 words (Cristia et al, 2013), 212 words (Gallagher, 2013) or 120 words (Finley & Badecker, 2009;Finley, 2011). Our study enriches the empirical picture by charting how the generalizations that participants make depend on the amount of exposure to the artificial language, in particular when given a very small amount of exposure: Participants in the One Set condition in Experiment 1 received only five exposure words, a fraction of the number of exposure words used in previous studies.…”

Section: Previous Studies Of Phonotactic Generalizationmentioning

confidence: 99%

See 4 more Smart Citations

Rapid generalization in phonotactic learning

Linzen

Gallagher

2017

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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Speakers judge novel strings to be better potential words of their language if those strings consist of sound sequences that are attested in the language. These intuitions are often generalized to new sequences that share some properties with attested ones: Participants exposed to an artificial language where all words start with the voiced stops [b] and [d] will prefer words that start with other voiced stops (e.g., [g]) to words that start with vowels or nasals. The current study tracks the evolution of generalization across sounds during the early stages of artificial language learning. In Experiments 1 and 2, participants received varying amounts of exposure to an artificial language. Learners rapidly generalized to new sounds: In fact, following short exposure to the language, attested patterns were not distinguished from unattested patterns that were similar in their phonological properties to the attested ones. Following additional exposure, participants showed an increasing preference for attested sounds, alongside sustained generalization to unattested ones. Finally, Experiment 3 tested whether participants can rapidly generalize to new sounds based on a single type of sound. We discuss the implications of our results for computational models of phonotactic learning.

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Section: Previous Studies Of Phonotactic Generalizationsupporting

confidence: 92%

Section: Mechanisms Of Generalizationsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 56%

Section: Introductionmentioning

confidence: 62%

Section: Previous Studies Of Phonotactic Generalizationmentioning

confidence: 99%

See 3 more Smart Citations

Rapid generalization in phonotactic learning

Linzen

Gallagher

2017

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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Speech Production and Perception

Baghai-Ravary

Beet

2012

SpringerBriefs in Electrical and Computer Engineering

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One way to investigate speech motor learning is to create artificial adaptation situations by perturbing speakers' auditory feedback in real time. Formant perturbations were introduced by Houde and Jordan (1998), providing the first evidence that speakers adapt their pronunciation to compensate for these perturbations. Twenty years later, this chapter provides an overview of the general impact of Houde and Jordan's work in speech research and beyond, as well as a more detailed review of studies that involve formant perturbations. The impact of Houde and Jordan's work appears to be cross-disciplinary. Although mainly related to speech production and perception, it has also been cited in the limb movement and even animal research, mainly as evidence of adaptive sensorimotor control. Formant perturbations research has expanded rapidly since 2006, spreading across the world and many research teams. We identified 77 experimental studies focused on formant perturbations which we then analyzed with regard to technical and theoretical issues. This analysis showed that various apparatuses and procedures were used to address important topics of speech research. A primary interest has been in feedback and feedforward control mechanisms in speech. These mechanisms were addressed in different populations, including adults and children with typical vs. atypical development, with behavioral or neurophysiological approaches, or both. Some formant perturbations studies more specifically focused on the integration of auditory and somatosensory feedback in speech production, while others explored the interaction between speech production and perception of phonemic contrasts. Some research questioned the processes and the nature of speech representations by investigating generalization of adaptation to formant perturbations. Finally, a few studies were interested in the effect of extraneous variables such as surface effects or speakers' general cognitive abilities. Altogether, these studies provide insights into speech motor control in general and into the understanding of sensorimotor interactions in particular. The field has developed recently and may still expand in the future, as it allows us to address fundamental topics in speech research such as perception-production links or abstract vs. exemplar representations. Future Caudrelier and Rochet-Capellan research with formant perturbations may also further connect sensorimotor adaptation to linguistic and cognitive factors and in particular to working and long-term memory.

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