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 ...

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

The company is exploring ways to improve voice-recognition technology for people who have impaired speech.

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 ...

Today, powered by the latest technologies like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, speech recognition is touching new milestones.

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 ...

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 ...

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.