To understand how hearing loss impacts people, researchers study people's ability to recognize speech. It is more difficult for people to recognize human speech if there is reverberation, some hearing impairment, or significant background noise, such as traffic noise or multiple speakers. As a result, hearing aid algorithms are often used to improve human speech recognition. To evaluate such algorithms, researchers perform experiments that aim to determine the signal-to-noise ratio at which a specific number of words (commonly 50%) are recognized. These tests, however, are time- and cost-intensive.

Hearing loss is a rapidly growing area of scientific research as the number of baby boomers dealing with hearing loss continues to increase as they age. To understand how hearing loss impacts people, researchers study people's ability to recognize speech. It is more difficult for people to recognize human speech if there is reverberation, some hearing impairment, or significant background noise, such as traffic noise or multiple speakers. As a result, hearing aid algorithms are often used to improve human speech recognition. To evaluate such algorithms, researchers perform experiments that aim to determine the signal-to-noise ratio at which a specific number of words (commonly 50%) are recognized.

Hearing loss is a rapidly growing area of scientific research as the number of baby boomers dealing with hearing loss continues to increase as they age. To understand how hearing loss impacts people, researchers study people's ability to recognize speech. It is more difficult for people to recognize human speech if there is reverberation, some hearing loss, or significant background noise, such as traffic noise or multiple speakers. As a result, hearing aid algorithms are often used to improve human speech recognition. To evaluate such algorithms, researchers perform experiments that aim to determine the signal-to-noise ratio at which a specific number of words (commonly 50%) are recognized.

For neuroscientist Professor Katharina von Kriegstein from TU Dresden, however, the human brain remains the "most admirable speech processing machine." "It works much better than computer-based speech processing and will probably continue to do so for a long time to come," comments Professor von Kriegstein, "because the exact processes of speech processing in the brain are still largely unknown." In a recent study, the neuroscientist from Dresden and her team discovered another building block in the mystery of human speech processing. In the study, 33 test persons were examined using functional magnetic resonance imaging (MRI). The test persons received speech signals from different speakers.

A new milestone in human speech recognition has been reached by Microsoft, matching the accuracy of trained human transcribers. The firm's software, used in its Cortana voice assistant, has achieved a 5.1 per cent margin of error, putting it on a par with professionals. One of the big frustrations of voice recognition has been getting machines to accept commands, a process which often involves repetition and exaggerated speech. The development means the company's products will soon accept orders with super-human precision. A new milestone in human speech recognition has been reached by Microsoft, matching the accuracy of trained human transcribers.