Apple, Google Among Tech Giants Committing To Improve Accessibility
Some of the biggest names in technology are part of a newly launched effort to expand accessibility of smartphones and other devices for those with disabilities.
Amazon, Apple, Google, Meta and Microsoft are joining with a handful of nonprofit organizations to support the Speech Accessibility Project, a research initiative at the University of Illinois Urbana-Champaign aimed at helping make voice recognition technology more useful for people with various disabilities.
Currently, voice assistants like Siri and Alexa and translation tools don’t always understand individuals with Down syndrome, cerebral palsy and other conditions that may impact speech patterns. Using artificial intelligence and machine learning, the new effort is looking to address that disparity.
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The Speech Accessibility Project will collect speech samples from people with a range of speech patterns, which will then be used to train machine-learning models.
All of the tech companies that have pledged support for the Speech Accessibility Project have committed to using data collected through the initiative to improve their voice recognition services, according to those behind the project.
“The option to communicate and operate devices with speech is crucial for anyone interacting with technology or the digital economy today,” said Mark Hasegawa-Johnson, a professor of electrical and computer engineering at the University of Illinois Urbana-Champaign who’s leading the project. “Speech interfaces should be available to everybody, and that includes people with disabilities.”
This is not the first time that a major tech company has tried to improve voice recognition for people with disabilities. Last year Google requested help from people with disabilities in testing an app developed to better decipher speech patterns of those with impairments. And, the company worked with the Canadian Down Syndrome Society in 2019 to collect speech samples from adults with Down syndrome to program its algorithm to better understand their unique speech patterns.
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