SONYC working with Downtown Brooklyn Alliance

SONYC are partnering with Downtown Brooklyn Partnership (DBP), a not-for-profit that manages three Business Improvement Districts in the area, to monitor noise pollution as part of a new “Living Lab” initiative. DBP president Regina Myrer said in a statement, “Smart city technology is making communities around the world safer, cleaner and more beautiful places to…

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SONYC featured in Popular Science

SONYC P.I. Juan Bello is interviewed in an article for Popular Science covering scientists’ approaches to noise pollution. In the interview he discusses why noise is tricky to deal with because, unlike water or air pollution, it leaves no traces behind in the environment, meaning that when people complain about evening construction noise, it can…

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SONYC presenting at Smart Cities Connect

SONYC will be one of NSF funded smart cities and communities of the future projects presenting and demonstrating our work at the sixth annual US Ignite Application Summit, co-located with the Smart Cities Connect Conference and Expo. The event takes place on March 27th at the Kansas City Convention Center. Further details can be found…

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New Publication: Investigating the Effect of Sound-Event Loudness on Crowdsourced Audio Annotations

Our paper “Investigating the Effect of Sound-Event Loudness on Crowdsourced Audio Annotations” has been accepted to IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018. Audio annotation is an important step in developing machine listening systems. It is also a time consuming process, which has motivated investigators to crowdsource audio…

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New Tools & Data for Soundscape Synthesis and Online Audio Annotation

We’re glad to announce the release of two open-source tools and a new dataset developed as part of the SONYC project we hope will be of use to the community:  Scaper: a library for soundscape synthesis and augmentation Automatically synthesize soundscapes with corresponding ground truth annotations  Useful for running controlled ML experiments (ASR, sound event detection, bioacoustic…

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