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Source separation technology is important for hearing aids to distinguish different noises in crowded environments. Poor programming can lead to discomfort and people turning off their aids. Speech recognition and music recording also use source separation algorithms.
Source separation is the distinction of multiple sources in a signal to allow one or more to be chosen while discarding the others. This has important implications for the development of hearing aids that will allow people to distinguish different noises in an environment such as a party or train station. The more sources there are, the more difficult it can be to clean up the signal to get meaningful data. Applications, including speech recognition software, also use source separation to provide more convenience to users.
This phenomenon is illustrated by the so-called “cocktail party problem”. People in a crowded room often have trouble separating the myriad sounds of noise, including people talking, musicians, footsteps, and other sources of sound. For people with good hearing, you can drill down and focus on a particular voice, such as a single speaker. People with hearing impairments may have issues with source separation and may need assistance such as hearing aids to navigate crowded, noisy spaces.
Hearing aids don’t just turn up the volume to make everything more audible. They also send signals to some auditory processing before routing them into the ear. They need source separation technology to separate the different sounds in a room and determine which one the listener is most likely to want to be able to hear. Someone nearby’s voice should have a higher value than a conversation in another part of the room, for example.
If hearing aids are not well programmed, they can be very uncomfortable to wear. They can deliver a jumble of noise without a single significant signal and can make it impossible for people to hear what’s going on around them. Poor signal processing can lead people to turn off their aids for convenience, which defeats the purpose of wearing them in the first place. The development of advanced source separation technology allows for greater precision in the design of hearing aids to extract voices and reduce other sounds.
A variety of source separation algorithms can be used not only on hearing aids, but on other auditory processing devices. Speech recognition systems must be able to extract voices from background noise, for example. Musicians work with source separation to clean up recordings. Restoring old recordings can also involve signal processing to extract meaningful sounds, like a trumpeter in a jazz band, and muting unwanted noise, like a waitress dropping a glass.
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