Does Musical Experience Facilitate Phonetic Accommodation During Human–Robot Interaction?
Published In: Journal of Speech, Language & Hearing Research, 2025, v. 68, n. 5. P. 2259 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Yitian Hong; Si Chen; Han Jiang 3 of 3
Abstract
Purpose: This study investigated the effect of musical training on phonetic accommodation in a second language (L2) after interacting with a social robot, exploring the motivations and reasons behind their accommodation strategies. Method: Fifteen L2 English speakers with long-term musical training experience (musician group) and 15 speakers without musical training experience (nonmusician group) were recruited to complete four conversational tasks with the social robot Furhat. Their production of a list of key words and carrier sentences was collected before and after conversations and used to quantify their phonetic accommodations. The spectral cues and prosodic cues of the production were extracted and analyzed. Results: Both groups showed similar convergence patterns but different divergence patterns. Specifically, the musician group showed divergence from the robot’s production on more prosodic cues (mean fundamental frequency and duration) than the nonmusician group. Both groups converged their vowel formants toward the robot without group differences. Conclusions: The findings reflect individuals’ assessment of the robot’s speech characteristics and their efforts to enhance communication efficiency, which might indicate a special speech register used for addressing the robot. The finding is more noticeable in the musician group compared to the nonmusician group. We proposed two possible explanations of the effect of musical training on phonetic accommodations: one involves the training of auditory attention and working memory and the other relates to the refinement of phonetic talent in L2 acquisition, contributing to theories on the relationship between music and language. This study also has implications for applying musical training to speech communication training in clinical populations and for designing social robots to better serve as speech therapy partners. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Speech, Language & Hearing Research. 2025/05, Vol. 68, Issue 5, p2259
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2025
- ISSN:1092-4388
- DOI:10.1044/2025_JSLHR-24-00495
- Accession Number:185140621
- Copyright Statement:Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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