AI & ML
Intonation Perception in Real and Synthetic Speech across Varying Familiarity Levels: A Pilot Study of Equivalence Assessment
arXiv cs.HC0 views
arXiv:2610.08839v1 Announce Type: cross Abstract: Language training relies on a corpus constructed by a large number linguistic materials. AI-powered voice clones provide a way to construct the corpus with relatively low cost. Singing voice conversion (SVC) model is used to generate synthetic voices. This study compares participants' performances on natural and synthetic speech in two experiments, similarity perception and intonation recognition. In the accuracy of similarity perception task, a significant interaction between speech type and intonation is found, suggesting that question may serve as a cue for speaker identification but may be influenced by synthetic features. In the accuracy of intonation recognition task, a significant interaction between speech type and familiarity is observed, indicating that speech type affects how much familiarity contributes to voice processing.
Source:https://arxiv.org/abs/2610.08839PreviousHow assigned AI use before class shapes active student engagement in classNextHow Could AI Eliminate Humanity? A Failure-Mode Analysis of Civilizational Risk
Related posts
Amazon Alexa for Shopping tools detailed ahead of Black Friday on November 27
0dev.to News
O cliente pediu desconto no pastel artesanal de R$ 15, mas pagou R$ 40 num hambúrguer sem reclamar
0dev.to Design
How do you actually track profit on your online store?
0dev.to Discuss
Google Tests Gemini 4 Carbon In Secret To See If People Like It
0dev.to Machine Learning
AI Agents Burn More Cash The Longer They Work For You
0dev.to Machine Learning

ElevenLabs em reais: quanto sai uma locução de 10 minutos
0dev.to Tutorial