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Sketching the Landscape of Speech Perception Research (2000–2020): A Bibliometric Study

Based on 6,407 speech perception research articles published between 2000 and 2020, a bibliometric analysis was conducted to identify leading countries, research institutes, researchers, research collaboration networks, high impact research articles, central research themes and trends in speech perc...

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Detalles Bibliográficos
Autores principales: Chen, Juqiang, Chang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201966/
https://www.ncbi.nlm.nih.gov/pubmed/35719567
http://dx.doi.org/10.3389/fpsyg.2022.822241
Descripción
Sumario:Based on 6,407 speech perception research articles published between 2000 and 2020, a bibliometric analysis was conducted to identify leading countries, research institutes, researchers, research collaboration networks, high impact research articles, central research themes and trends in speech perception research. Analysis of highly cited articles and researchers indicated three foundational theoretical approaches to speech perception, that is the motor theory, the direct realism and the computational approach as well as four non-native speech perception models, that is the Speech Learning Model, the Perceptual Assimilation Model, the Native Language Magnet model, and the Second Language Linguistic Perception model. Citation networks, term frequency analysis and co-word networks revealed several central research topics: audio-visual speech perception, spoken word recognition, bilingual and infant/child speech perception and learning. Two directions for future research were also identified: (1) speech perception by clinical populations, such as hearing loss children with cochlear implants and speech perception across lifespan, including infants and aged population; (2) application of neurocognitive techniques in investigating activation of different brain regions during speech perception. Our bibliometric analysis can facilitate research advancements and future collaborations among linguists, psychologists and brain scientists by offering a bird view of this interdisciplinary field.