Author: Monica Chin
Photo by Dan Seifert / The Verge
Speech recognition systems have more trouble understanding black users’ voices than those of white users, according to a new Stanford study.
The researchers used voice recognition tools from Apple, Amazon, Google, IBM, and Microsoft to transcribe interviews with 42 white people and 73 black people, all of which took place in the US. The tools misidentified words about 19 percent of the time during the interviews with white people and 35 percent of the time during the interviews with black people. The system found 2 percent of audio snippets from white people to be unreadable, compared to 20 percent of those from black people. The errors were particularly large for black men, with an error rate of 41 percent compared to 30 percent for...
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Speech recognition systems have more trouble understanding black users’ voices than those of white users, according to a new Stanford study.
The researchers used voice recognition tools from Apple, Amazon, Google, IBM, and Microsoft to transcribe interviews with 42 white people and 73 black people, all of which took place in the US. The tools misidentified words about 19 percent of the time during the interviews with white people and 35 percent of the time during the interviews with black people. The system found 2 percent of audio snippets from white people to be unreadable, compared to 20 percent of those from black people. The errors were particularly large for black men, with an error rate of 41 percent compared to 30 percent for...
Continue reading…
Continue reading...