Healthcare-ready voice tech boosts efficiency, protects sensitive data, and integrates seamlessly into clinical workflows.

Voice recognition meets artificial intelligence With the continually improving computing power and compact size of mobile processors, large vocabulary engines that promote the use of natural speech ...

A machine learning model was more accurate than 12 experienced endocrinologists in identifying adults with acromegaly based on voice recordings, according to findings published in The Journal of ...

By using personalized voice models, its AI-powered speech recognition system helps people with speech impairments, caused by conditions like cerebral palsy, Parkinson’s, Down Syndrome or stroke ...

--Fluent.ai, a leader in embedded speech recognition solutions, today announces its expanded partnership and collaboration with Knowles Corporation, a market leader and global provider of advanced ...

By using personalized voice models, its AI-powered speech recognition system helps people with speech impairments, caused by conditions like cerebral palsy, Parkinson’s, Down Syndrome or stroke ...

Ultimately, the accent gap in voice recognition is a data problem. The higher the quantity and diversity of speech samples in a corpus, the more accurate the resulting model — at least in theory.

Modern systems use advanced AI models trained on massive datasets to understand diverse accents, dialects, and languages, improving accuracy over time. Examples of Voice Recognition ...