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"Machine listening" is one common term for a fast-growing interdisciplinary field of science and engineering which uses audio signal processing and machine learning to "make sense" of sound and speech.[^Cella, Serizel, Ellis] Machine listening is what enables you to be "understood" by Siri and Alexa, to Shazam a song, and to interact with many audio-assistive technologies if you are blind or vision impaired.[^alper] As early as the 90s, the term was already being used in computer music to describe the analytic dimension of ['interactive music systems'](https://wp.nyu.edu/robert_rowe/text/interactive-music-systems-1993/chapter5/),[^rowe] whose behavior changes in response to live musical input, though there are  even before that.[^maier_audio_1] Machine Listening was also, of course, a cornerstone of the mass surveillance programs revealed by Edward Snowden in 2013: SPIRITFIRE's "speech-to-text keyword search and paired dialogue transcription"; EViTAP's "automated news monitoring"; VoiceRT's "ingestion", according to one NSA slide, of Iraqi voice data into voiceprints. Domestically, machine listening technologies underpin the vast databases of vocal biometrics now held by many [prison providers](https://theintercept.com/2019/01/30/prison-voice-prints-databases-securus/ "Prisons Across the U.S. Are Quietly Building Databases of Incarcerated People’s Voice Prints") and, for instance, the [Australian Tax Office](https://www.computerworld.com/article/3474235/the-ato-now-holds-the-voiceprints-of-one-in-seven-australians.html "The ATO now holds the voiceprints of one in seven Australians"). And they are quickly being integrated into infrastructures of development, security and policing. |
