Impaired Prosodic Processing but Not Hearing Function Is Associated with an Age-Related Reduction in AI Speech Recognition

Background/Objectives: Voice artificial intelligence (AI) technology is becoming increasingly common. Recent work indicates that middle-aged to older adults are less able to identify modern AI speech compared to younger adults, but the underlying causes are unclear. Methods: The current study with y...

Full description

Saved in:
Bibliographic Details
Main Authors: Björn Herrmann, Mo Eric Cui
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Audiology Research
Subjects:
Online Access:https://www.mdpi.com/2039-4349/15/1/14
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background/Objectives: Voice artificial intelligence (AI) technology is becoming increasingly common. Recent work indicates that middle-aged to older adults are less able to identify modern AI speech compared to younger adults, but the underlying causes are unclear. Methods: The current study with younger and middle-aged to older adults investigated factors that could explain the age-related reduction in AI speech identification. Experiment 1 investigated whether high-frequency information in speech—to which middle-aged to older adults often have less access due sensitivity loss at high frequencies—contributes to age-group differences. Experiment 2 investigated whether an age-related reduction in the ability to process prosodic information in speech predicts the reduction in AI speech identification. Results: Results for Experiment 1 show that middle-aged to older adults are less able to identify AI speech for both full-bandwidth speech and speech for which information above 4 kHz is removed, making the contribution of high-frequency hearing loss unlikely. Experiment 2 shows that the ability to identify AI speech is greater in individuals who also show a greater ability to identify emotions from prosodic speech information, after accounting for hearing function and self-rated experience with voice-AI systems. Conclusions: The current results suggest that the ability to identify AI speech is related to the accurate processing of prosodic information.
ISSN:2039-4349