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Purpose: Speech rate convergence has been reported previously as a phenomenon in which one's speech rate is influenced by his/her partner's speech rate. This phenomenon has been demonstrated in artificial settings, and to some extent, in mother-child interactions. The purpose of this study was to explore speech rate adjustment in a quasi-natural adult-adult conversation.
Methods: An A-B-A-B paradigm was used, in which ten adults conversed on a given topic with two experimenters. Speech rates of both communication partners were measured.
Results: Participants significantly reduced their speech rate, in response to the experimenters' reduction in speech rate. However, the participants' reduction in speech rate was significantly smaller than the experimenters' reduction in speech rate. In addition, during the controlled slow speech rate, the participants' speech rate correlated negatively with that of the experimenters'.
Conclusion: Results suggest that speech rate convergence is a non-linear phenomenon, and may be affected by various linguistic as well as communicational factors. From a clinical perspective, the results support the use of the modeling strategy in speech therapy, as a means to facilitate a reduction in clients' speech rate.
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http://dx.doi.org/10.1016/j.jfludis.2018.06.002 | DOI Listing |
Folia Phoniatr Logop
March 2025
Introduction: Newborn cries exhibit a richness of melody and rhythmicity, yet their rhythmic features have been less studied.
Methods: In this study, we analyzed the amplitude modulation of 1,884 cries from 30 Chinese newborns.
Results: The group-averaged amplitude modulation spectrum revealed an evident increase in energy between 0.
Eur Arch Otorhinolaryngol
March 2025
Otolaryngology Research Center, Department of Otolaryngology-Head and Neck Surgery, Tehran University of Medical Sciences, Imam Khomeini Medical Complex, Tehran, Iran.
Purpose: To evaluate the ototoxicity of povidone iodine (PVP-I) at concentrations of 5% and 10% during tympanoplasty by assessing frequency-specific audiometric outcomes and graft success rates in a large cohort of patients.
Methods: This prospective, triple-blinded, randomized clinical trial enrolled 542 patients undergoing primary tympanoplasty. After excluding patients for inadequate follow-up, 204 ears received 10% PVP-I and 199 ears received 5% PVP-I.
Cortex
March 2025
Queensland Brain Institute, The University of Queensland, Brisbane, Australia.
Older adults can find verbal communication in noisy environments challenging, but the underlying cognitive phenomena and the specific mechanisms contributing to age-related decline remain unclear. Using a newly designed propositional speech production paradigm, we examined how semantic distractors of varying levels of relatedness affect propositional speech performance in healthy adults. In the paradigm, participants were assessed on their ability to formulate verbal responses while distracted by semantically related or unrelated words, simulating real-world scenarios with meaningful auditory distractions (e.
View Article and Find Full Text PDFMov Disord Clin Pract
March 2025
Innovative Therapies in Pediatric Neurology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain.
Background: Myoclonus-dystonia syndrome (MDS) is a genetic movement disorder with childhood-onset, most frequently caused by SGCE defects.
Objective: To evaluate the diagnostic and treatment strategies in MDS used by experts from the European Reference Network for rare neurological diseases (ERN-RND), and to assess the diagnosis and management experience in patients with MDS.
Methods: Two different questionnaires were distributed: one among neurologists from ERN-RND, and another among patients and families with SGCE-related MDS.
Comput Biol Med
March 2025
Centre for Language and Speech Technology (CLST), Radboud University Nijmegen, The Netherlands; Centre for Language Studies (CLS), Radboud University Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, The Netherlands. Electronic address:
Machine learning (ML) and Deep Neural Networks (DNN) have greatly aided the problem of Automatic Speech Recognition (ASR). However, accurate ASR for dysarthric speech remains a serious challenge. The dearth of usable data remains a problem in applying ML and DNN techniques for dysarthric speech recognition.
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