Dynamic Sound Identification

TitleDynamic Sound Identification
Publication TypeCase Study
Year of Publication2018
AuthorsPrinceton University, Center on Human Values
PublisherPrinceton University, Center on Human Values
Place PublishedDialogues on AI and Ethics
AbstractAlso known as “query-by-example,” dynamic sound recognition recently found commercial success as a means to identify music through short audio snippets, captured through a microphone. First-generation algorithms recognized unique signatures in a particular sound, which they could then match with a most likely source or an equivalent sound stored in a large database of previously identified auditory signatures. Early mobile apps employing these algorithms were amusing and effectively enabled music listeners to identify a song’s title and the performing artist. A company took this idea and launched a mobile app called Epimetheus that can also be used to identify all kinds of different sounds including specific human voices, bird calls and many other sounds. When an issue emerges in testing where the voice of a transgender individual is classified by her biological sex, the researchers try to figure out how to deal with errors that might cause major harm members of already marginalized groups.
URLhttps://aiethics.princeton.edu/case-studies/#gallery-2

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