Language experience confers a benefit to voice learning, a concept described in the literature as the language familiarity effect (LFE). What experiences are necessary for the LFE to be conferred is less clear. We contribute empirically and theoretically to this debate by examining within and across language voice learning with Cantonese-English bilingual voices in a talker-voice association paradigm. Listeners were trained in Cantonese or English and assessed on their abilities to generalize voice learning at test on Cantonese and English utterances. By testing listeners from four language backgrounds - English Monolingual, Cantonese-English Multilingual, Tone Multilingual, and Non-tone Multilingual groups - we assess whether the LFE and group-level differences in voice learning are due to varying abilities (1) in accessing the relative acoustic-phonetic features that distinguish a voice, (2) learning at a given rate, or (3) generalizing learning of talker-voice associations to novel same-language and different-language utterances. The specific four language background groups allow us to investigate the roles of language-specific familiarity, tone language experience, and generic multilingual experience in voice learning. Differences in performance across listener groups shows evidence in support of the LFE and the role of two mechanisms for voice learning: the extraction and association of talker-specific, language-general information that is more robustly generalized across languages, and talker-specific, language-specific information that may be more readily accessible and learnable, but due to its language-specific nature, is less able to be extended to another language.
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http://dx.doi.org/10.1016/j.cognition.2024.105866 | DOI Listing |
Sensors (Basel)
January 2025
School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, UK.
Elephant sound identification is crucial in wildlife conservation and ecological research. The identification of elephant vocalizations provides insights into the behavior, social dynamics, and emotional expressions, leading to elephant conservation. This study addresses elephant sound classification utilizing raw audio processing.
View Article and Find Full Text PDFLife (Basel)
December 2024
Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital, Massachusetts General Hospital, Harvard Medical School, 1575 Cambridge Street, Cambridge, MA 02115, USA.
Background: This study aimed to explore the potential associations between voice metrics of patients with PD and their motor symptoms.
Methods: Motor and vocal data including the Unified Parkinson's Disease Rating Scale part III (UPDRS-III), Harmonic-Noise Ratio (HNR), jitter, shimmer, and smoothed cepstral peak prominence (CPPS) were analyzed through exploratory correlations followed by univariate linear regression analyses. We employed these four voice metrics as independent variables and the total and sub-scores of the UPDRS-III as dependent variables.
Acad Emerg Med
January 2025
Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Background: Prehospital emergencies require providers to rapidly identify patients' medical condition and determine treatment needs. We tested whether medics' initial, written impressions of patient condition contain information that can help identify patients who require prehospital lifesaving interventions (LSI) prior to or during transport.
Methods: We analyzed free-text medic impressions of prehospital patients encountered at the scene of an accident or injury, using data from STAT MedEvac air medical transport service from 2012 to 2021.
PLoS One
January 2025
Department of Teacher Education, University of Jyväskylä, Jyväskylä, Finland.
The aim of the study was to find whether certain meaningful moments in the learning process are noticeable through features of voice and how acoustic voice analyses can be utilized in learning research. The material consisted of recordings of nine university students as they were completing tasks concerning direct electric circuits as part of their course of teacher education in physics. Prosodic features of voice-fundamental frequency (F0), sound pressure level (SPL), acoustic voice quality measured by LTAS, and pausing-were investigated.
View Article and Find Full Text PDFJ Interprof Care
January 2025
De Montfort University, Leicester, UK.
The main goal of interprofessional education (IPE) is to improve services and the quality of care for patients, their families, and communities. Enabling different professional learners, or others with relevant care roles, to learn together, is expected to advance care delivery. For both pre and post-registration learning, it therefore follows that listening to and working with service users is essential to underpin interprofessional learning.
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