Audio Analytic is a British company headquartered in Cambridge, England that has developed a patented sound recognition software framework called ai3, which provides technology with the ability to understand context through sound. This framework includes an embeddable software platform that can react to a range of sounds such as smoke alarms and carbon monoxide alarms, window breakage, infant crying and dogs barking.

Audio Analytic
Company typePrivate
IndustrySoftware, Embedded
FoundedCambridge, UK (2010 (2010)) Series A Investment
FounderDr. Christopher Mitchell (CEO)
HeadquartersCambridge, UK
Key people
Dr. Robert Swann (chairman) Alphamosaic, Amy Weatherup (director)
ProductsSound Recognition Systems
Websitewww.audioanalytic.com

History

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The company was based on founder Christopher Mitchell's doctoral research from Anglia Ruskin University, with seed investment from EEDA (East of England Development Agency) and local Cambridge Angels investors.[citation needed]

In 2022 Audio Analytic was bought by Facebook and Instagram owner Meta.[1]

Products

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Audio Analytic sells ai3, a software package that is embedded on a device, along with an assortment of sound profiles that the software can recognise, including warning alarms, window breakage, an infant crying, and voice activity.[2]

Audio Analytic developed the Polyphonic Sound Detection Score (PSDS), a metric for evaluating the performance of sound recognition algorithms when applied to polyphonic sound recordings.[3][4][5] They also released an accompanying software framework that implements the PSDS.[6]

References

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  1. ^ Field, Matthew (6 November 2022). "Cambridge start-up is bought by Facebook owner as Zuckerberg pushes deeper into the metaverse". The Telegraph. ISSN 0307-1235. Retrieved 7 November 2022.
  2. ^ Bedingfield, Will (5 September 2019). "AI sound recognition will help protect your home from burglary". Wired UK. ISSN 1357-0978. Retrieved 1 October 2020.
  3. ^ Bilen, Cagdas; Ferroni, Giacomo; Tuveri, Francesco; Azcarreta, Juan; Krstulovic, Sacha (May 2020). "A Framework for the Robust Evaluation of Sound Event Detection". ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 61–65. arXiv:1910.08440. doi:10.1109/ICASSP40776.2020.9052995. ISBN 978-1-5090-6631-5. S2CID 204788761.
  4. ^ DCase 2020 Challenges. "Sound event detection and separation in domestic environments - DCASE". dcase.community. Retrieved 4 August 2020.{{cite web}}: CS1 maint: numeric names: authors list (link)
  5. ^ Wisdom, Scott; Erdogan, Fonseca, Eduardo and Salamon, Justin and Seetharaman, Prem and Hershey, John R., Hakan; Ellis, Daniel P. W.; Serizel, Romain; Turpault, Nicolas; Fonseca, Eduardo; Salamon, Justin; Seetharaman, Prem; Hershey, John R. (2020). "What's All the FUSS About Free Universal Sound Separation Data?". In Preparation.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  6. ^ Audio Analytic (22 July 2020). "audioanalytic/psds_eval GitHub repository". GitHub. Audio Analytic. Retrieved 4 August 2020.
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