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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.
Company type | Private |
---|---|
Industry | Software, Embedded |
Founded | Cambridge, UK (2010 ) Series A Investment |
Founder | Dr. Christopher Mitchell (CEO) |
Headquarters | Cambridge, UK |
Key people | Dr. Robert Swann (chairman) Alphamosaic, Amy Weatherup (director) |
Products | Sound Recognition Systems |
Website | www |
History
editThe 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
editAudio 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
edit- ^ 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.
- ^ Bedingfield, Will (5 September 2019). "AI sound recognition will help protect your home from burglary". Wired UK. ISSN 1357-0978. Retrieved 1 October 2020.
- ^ 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.
- ^ DCase 2020 Challenges. "Sound event detection and separation in domestic environments - DCASE". dcase.community. Retrieved 4 August 2020.
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: CS1 maint: numeric names: authors list (link) - ^ 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.
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: CS1 maint: multiple names: authors list (link) - ^ Audio Analytic (22 July 2020). "audioanalytic/psds_eval GitHub repository". GitHub. Audio Analytic. Retrieved 4 August 2020.
External links
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