Posted by Samuel J. Yang, Research Scientist and Dick Lyon, Principal Scientist, Google Research
For the ~466 million people in the world who are deaf or hard of hearing, the lack of easy access to accessibility services can be a barrier to participating in spoken conversations encountered daily. While hearing aids can help alleviate this, simply amplifying sound is insufficient for many. One additional option that may be available is the cochlear implant (CI), which is an electronic device that is surgically inserted into a part of the inner ear, called the cochlea, and stimulates the auditory nerve electrically via external sound processors. While many individuals with these cochlear implants can learn to interpret these electrical stimulations as audible speech, the listening experience can be quite varied and particularly challenging in noisy environments.
Modern cochlear implants drive electrodes with pulsatile signals (i.e., discrete stimulation pulses) that are computed by external sound processors. The main challenge still facing the CI field is how to best process sounds — to convert sounds to pulses on electrodes — in a way that makes them more intelligible to users. Recently, to stimulate progress on this problem, scientists in industry and academia organized a CI Hackathon to open the problem up to a wider range of ideas.
In this post, we share exploratory research demonstrating that a speech enhancement preprocessor — specifically, a noise suppressor — can be used at the input of a CI’s processor to enhance users’ understanding of speech in noisy environments. We also discuss how we built on this work in our entry for the CI Hackathon and how we will continue developing this work.
Improving CIs with Noise Suppression
In 2019, a small internal project demonstrated the benefits of noise suppression at the input of a CI’s processor. In this project, participants listened to 60 pre-recorded and pre-processed audio samples and
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