A hearing aid technology has been developed that scans your facial movements and uses an artificial intelligence (AI) to work out what is being said. Developed by engineers at the University of Glasgow, the system is even able to read the lips of people who are wearing a mask. The team trained algorithms with data collected by scanning people's faces with radar and Wi-Fi signals while they were speaking. This allowed the system to correctly interpret speech up to 95 per cent of the time for unmasked lips, and up to 83 per cent of the time with a mask. If integrated into hearing aids, it could help deaf and hard-of-hearing people to focus on sounds more easily in noisy environments.

Machine learning algorithms could one day be used to improve speech recognition in hearing-impaired people, researchers in Germany have shown. Using a novel algorithm, Jana Roßbach and colleagues at Carl von Ossietzky University could accurately predict when people with both normal hearing, and those with different levels of hearing impairment would mishear over 50% of words in a variety of noisy environments – an important test of hearing-aid efficacy. The lives of many hearing-impaired people have been significantly improved by hearing aid algorithms, which digitize and process sounds before delivering an amplified version into the ear. A key challenge still faced by this technology is improving the devices' ability to differentiate between human speech and background noise – something that is done using digital signal-processing algorithms. Researchers often use listening experiments to evaluate the ability of hearing aid algorithms to recognize speech.

The research follows similar work published by a separate group at the University of Oxford earlier this month. Using related techniques, these scientists were able to create a lip-reading program called LipNet that achieved 93.4 percent accuracy in tests, compared to 52.3 percent human accuracy. However, LipNet was only tested on specially-recorded footage that used volunteers speaking formulaic sentences. By comparison, DeepMind's software -- known as "Watch, Listen, Attend, and Spell" -- was tested on far more challenging footage; transcribing natural, unscripted conversations from BBC politics shows.DeepMind's AI program was trained on 5,000 hours of TV More than 5,000 hours of footage from TV shows including Newsnight, Question Time, and the World Today, was used to train DeepMind's "Watch, Listen, Attend, and Spell" program. The videos included 118,000 difference sentences and some 17,500 unique words, compared to LipNet's test database of video of just 51 unique words.