The research team from University of East Anglia compared the performance of a machine-based lip-reading system with that of 19 human lip-readers.

They found that the automated system significantly outperformed the human lip-readers – scoring a recognition rate of 80 per cent, compared with only 32 per cent for human viewers on the same task.

Unlike the traditional approach to lip-reading training, where viewers are taught to spot key lip-shapes from static (often drawn) images, the new video-based training system significantly improved their ability to lip-read monosyllabic words.

"This pilot study is the first time an automated lip-reading system has been benchmarked against human lip-readers and the results are perhaps surprising," said the study''s lead author Sarah Hilder.

"With just four hours of training it helped them improve their lip-reading skills markedly.

"We hope this research will represent a real technological advance for the deaf community," she added.

"This research confirms how difficult the vital skill of lip-reading is to learn," said Agnes Hoctor, campaigns manager at the RNID.

"We would welcome the development of video-based or online training resources to supplement the teaching of lip-reading.

"Hearing loss affects 55 per cent of people over 60 so, with the ageing population, demand to learn lip-reading is only going to increase," Hoctor added.