Whisper comprises nine models of different sizes and capabilities. These models are trained for speech recognition and translation tasks, capable of transcribing speech audio into text and ...

Previous speech recognition systems were modeled on adult voices and lacked the accuracy required for an educational context. The kid-specific speech recognition that now powers oral reading fluency ...

To develop Whisper-Medusa speech recognition model, aiOla modified Whisper’s architecture to add a multi-head attention mechanism.

More information: Michael McGuire et al, Assessing Whisper automatic speech recognition and WER scoring for elicited imitation: Steps toward automation, Research Methods in Applied Linguistics (2025).

Speech recognition remains a challenging problem in AI and machine learning. In a step toward solving it, OpenAI today open-sourced Whisper, an automatic speech recognition system that the company ...

Automated systems cannot be trusted to make decisions the way federal workers—actual people—can. Historically, hallucination hasn’t been a major issue in speech recognition.

Most computerized speech recognition systems can understand what a human says up to 98 percent of the time, and yet people still chafe at using automated phone help-desk systems. The key to making ...

One group commonly misunderstood by voice technology are individuals who speak African American English, or AAE. Researchers designed an experiment to test how AAE speakers adapt their speech when ...

Natural speech recognition is what most people want and that’s a challenge that has yet to be met in a way for it to be widely adopted. We’re surrounded by options that offer some form of ...

The Speech Accessibility Project will use artificial intelligence and machine learning to make speech recognition systems more inclusive of different speech patterns. Amazon, Apple, Google, Meta ...