A role for the developing lexicon in phonetic category acquisition.

Feldman, Naomi H.; Griffiths, Thomas L.; Goldwater, Sharon; Morgan, James L.

doi:10.1037/a0034245

Cited by 163 publications

(189 citation statements)

References 116 publications

(255 reference statements)

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“…Accounts based purely on statistical distributions of acoustic cues would have difficulty explaining the formation of separate categories in such cases where acoustic information from two speech categories is very similar. Recent evidence from computational models also suggests that acoustic distributional information alone may not be sufficient for phonetic category acquisition (Feldman, Myers, White, Griffiths, & Morgan, 2011;McMurray, Aslin, & Toscano, 2009a). Feldman et al (2011) suggest that phonetic category development occurs as part of extracting meaning from language, through association of phonetic distributions with lexical items.…”

Section: Discussionmentioning

confidence: 99%

“…Recent evidence from computational models also suggests that acoustic distributional information alone may not be sufficient for phonetic category acquisition (Feldman, Myers, White, Griffiths, & Morgan, 2011;McMurray, Aslin, & Toscano, 2009a). Feldman et al (2011) suggest that phonetic category development occurs as part of extracting meaning from language, through association of phonetic distributions with lexical items. Association with the meanings (and orthography) of the respective characters can explain how different speech categories, such as T2 and T3 sandhi, can form separate representations at the category level, despite very similar acoustic distributions.…”

Section: Discussionmentioning

confidence: 99%

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Multi-level processing of phonetic variants in speech production and visual word processing: evidence from Mandarin lexical tones

Nixon

Chen

Schiller

2014

Language, Cognition and Neuroscience

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Two picture-word interference experiments provide new evidence on the nature of phonological processing in speech production and visual word processing. In both experiments, responses were significantly faster either when distractor and target matched in tone category, but had different overt realisations (toneme condition) or when target and distractor matched in overt realisation, but mismatched in tone category (contour condition). Tone 3 sandhi is an allophone of Beijing Mandarin Tone 3 (T3). Its contour is similar to another tone, Tone 2. In Experiment 1, sandhi picture naming was faster with contour (Tone 2) and toneme (low Tone 3) distractors, compared to control distractors. This indicates both category and context-specific representations are activated in sandhi word production. In Experiment 2, both contour (Tone 2) and toneme (low Tone 3) picture naming was facilitated by visually presented sandhi distractors, compared to controls, evidence that category and context-specific instantiated representations are automatically activated during processing of visually presented words. Combined, the results point to multi-level processing of phonology, whether words are overtly produced or processed visually. Interestingly, there were differences in the time course of effects.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Multi-level processing of phonetic variants in speech production and visual word processing: evidence from Mandarin lexical tones

Nixon

Chen

Schiller

2014

Language, Cognition and Neuroscience

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“…In the past decades, researchers have focused on two possible mechanisms that could account for this phonetic learning. One account focuses on infants' sensitivity to the frequency distributions of sounds (e.g., Maye, Werker, & Gerken, 2002), while another focuses on the possibility that infants learn phonetic contrasts from contrastive lexical items (e.g., Feldman, Griffiths, Goldwater, & Morgan, 2013). …”

Section: Introductionmentioning

confidence: 99%

Semantics guide infants’ vowel learning: Computational and experimental evidence

Schure

Junge

Boersma

2016

Infant Behavior and Development

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Semantics guide infants' vowel learning: computational and experimental evidenceter Schure, S.M.M.; Junge, C.M.M.; Boersma, P.P.G. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. a b s t r a c tIn their first year, infants' perceptual abilities zoom in on only those speech sound contrasts that are relevant for their language. Infants' lexicons do not yet contain sufficient minimal pairs to explain this phonetic categorization process. Therefore, researchers suggested a bottom-up learning mechanism: infants create categories aligned with the frequency distributions of sounds in their input. Recent evidence shows that this bottom-up mechanism may be complemented by the semantic context in which speech sounds occur, such as simultaneously present objects. To test this hypothesis, we investigated whether discrimination of a non-native vowel contrast improves when sounds from the contrast were paired consistently or randomly with two distinct visually presented objects, while the distribution of speech tokens suggested a single broad category. This was assessed in two ways: computationally, namely in a neural network simulation, and experimentally, namely in a group of 8-month-old infants. The neural network, trained with a large set of sound-meaning pairs, revealed that two categories emerge only if sounds are consistently paired with objects. A group of 49 real 8-month-old infants did not immediately show sensitivity to the pairing condition; a later test at 18 months with some of the same infants, however, showed that this sensitivity at 8 months interacted with their vocabulary size at 18 months. This interaction can be explained by the idea that infants with larger future vocabularies are more positively influenced by consistent training (and/or more negatively influenced by inconsistent training) than infants with smaller future vocabularies. This suggests that consistent pairing with distinct visual objects can help infants to discriminate speech sounds even when the auditory information does not signal a distinction. Together our results give computational as well as experimental support for the idea that semantic context plays a role in disambiguating phonetic auditory input.

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“…In theory, semantic information could offer a valuable cue for phoneme induction 1 by helping infants distinguish between minimal pairs, as linguists do (Trubetzkoy, 1939). However, due to a widespread assumption that infants do not know the meanings of many words at the age when they are learning phonetic categories (see Swingley, 2009 for a review), most recent models of early phonetic category acquisition have explored the phonetic learning problem in the absence of semantic information (de Boer and Kuhl, 2003;Dillon et al, 2013;Feldman et al, 2013a;McMurray et al, 2009;Vallabha et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we explore the potential contribution of semantic information to phonetic learning by formalizing a model in which learners attend to the word-level context in which phones appear (as in the lexical-phonetic learning model of Feldman et al, 2013a) and also to the situations in which word-forms are used. The modeled situations consist of combinations of categories of salient activities or objects, similar to the activity contexts explored by Roy et al (2012), e.g.,'getting dressed' or 'eating breakfast'.…”

Section: Introductionmentioning

confidence: 99%

Weak semantic context helps phonetic learning in a model of infant language acquisition

Frank¹,

Feldman²,

Goldwater³

2014

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Learning phonetic categories is one of the first steps to learning a language, yet is hard to do using only distributional phonetic information. Semantics could potentially be useful, since words with different meanings have distinct phonetics, but it is unclear how many word meanings are known to infants learning phonetic categories. We show that attending to a weaker source of semantics, in the form of a distribution over topics in the current context, can lead to improvements in phonetic category learning. In our model, an extension of a previous model of joint word-form and phonetic category inference, the probability of word-forms is topic-dependent, enabling the model to find significantly better phonetic vowel categories and word-forms than a model with no semantic knowledge.

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A role for the developing lexicon in phonetic category acquisition.

Cited by 163 publications

References 116 publications

Multi-level processing of phonetic variants in speech production and visual word processing: evidence from Mandarin lexical tones

Multi-level processing of phonetic variants in speech production and visual word processing: evidence from Mandarin lexical tones

Semantics guide infants’ vowel learning: Computational and experimental evidence

Weak semantic context helps phonetic learning in a model of infant language acquisition

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