Speech recognition systems are deep-rooted with bias toward people of color, a new study reveals. Stanford researchers found these technologies from Amazon, Apple, Google, IBM and Microsoft make twice as many errors when interpreting language from black people than words spoken by whites. The team fed systems with nearly 2,000 speech samples from 115 individuals, 42 whites and 73 blacks, and found the average error rate for whites was 19 percent and 35 percent for blacks. Apple was found to perform the worst out of the group with a 45 percent error rate for black speakers and 23 percent for white speakers. Those involved with the study believed the inaccuracies are due to data sets used to train the systems are designed predominately by white people. Scroll down for video Stanford researchers found AI-powered voice recognition technologies from Amazon, Apple, Google, IBM and Microsoft make twice as many errors when interpreting language from black people than words spoken by whites Stanford University released the study Monday, which used recordings of black speech from the Corpus of Regional African American Language, and samples from white people came for Voices of California, which are recorded interviews of residents in different parts of… Read full this story
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AI speech recognition systems from five major tech companies are biased toward people of color, as they make twice as many errors transcribing speech from black people than they do from whites, study reveals have 340 words, post on www.dailymail.co.uk at March 24, 2020. This is cached page on SEO. If you want remove this page, please contact us.