Evidence map›Paper›PMID 41822139›Full record

ReviewNeurobiology of language (Cambridge, Mass.)2026

Embodied Speech: Sensorimotor Contributions to Native and Non-Native Phoneme Processing and Learning.

Tzuyi Tseng, Jennifer Krzonowski, Claudio Brozzoli, Alice C Roy, Véronique Boulenger

Abstract readReview
In one paragraph

Review in Neurobiology of language (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tzuyi TsengCNRS, Université Lyon 2, Laboratoire Dynamique du Langage, Lyon, France.ORCID https://orcid.org/0000-0001-6691-8680
Jennifer KrzonowskiCNRS, Université Lyon 2, Laboratoire Dynamique du Langage, Lyon, France.ORCID https://orcid.org/0000-0002-9926-8159
Claudio BrozzoliIntegrative Multisensory Perception Action & Cognition Team (ImpAct), Centre de Recherche en Neurosciences de Lyon, INSERM, Université Claude Bernard 1, Lyon, France.ORCID https://orcid.org/0000-0002-1719-8506
Alice C RoyCNRS, Université Lyon 2, Laboratoire Dynamique du Langage, Lyon, France.
Véronique BoulengerCNRS, Université Lyon 2, Laboratoire Dynamique du Langage, Lyon, France.ORCID https://orcid.org/0000-0001-8701-8278

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning to recognize and produce foreign speech sounds can be challenging, particularly when only subtle differences distinguish these new sounds from phonemes in the native language. Functional neuroimaging evidence shows that the motor cortex is involved in speech production and in perceptual phonemic processing. This highlights the embodied nature of speech perception, predicting the potential benefits of sensorimotor-based training approaches to enhance the acquisition of foreign speech sounds. Hence, here we first review current findings on the motor contribution to not only native but also non-native phoneme perception. Available evidence has established that motor cortical activity especially shows up under non-optimal perceptual conditions, such as when native phonemes are degraded by noise or when listeners perceive non-native speech sounds. Drawing upon this evidence, we then review training paradigms that have been developed for learning foreign phonemes, with a special emphasis on those embedding manual gestures as cues to represent phonetic features of the to-be-learned speech sounds. By pointing to both strengths and caveats of available studies, this review allows to delineate a clear framework and opens perspectives to optimize foreign phoneme learning, and ultimately support perception and production.

Indexed as

embodimentforeign language learningmanual gesturesmotor systemnon-native phonemesspeech perception

Identifiers

PMID41822139
PMCPMC12978677

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.