Author: Justin Salamon

WagnerTech, in partnership with NYU Tandon School of Engineering, The GovLab and the NYU Center for Data Science, invites you to hear first-hand from tech enthusiasts playing lead roles in their field, about how they are leveraging technology to advance high-impact innovation for the public good.

How is technology being used to trigger social change? What are its latest applications/trends for policy makers, community organizers, data scientists and civic advocates?

Kick started by lightning talks by members of the NYU community holding tech leadership roles in different sectors, the meetup will be followed by one hour of networking among speakers and attendees.
Lightning talks by:

• Noelle Francois, Executive Director, Heat Seek NYC
• Chris Whong, Adjunct Assistant Professor of Urban Planning at Wagner
• Justin Salamon, Post Doctoral Associate at the Center for Urban Science and Progress
• Milena Berry, Co-Founder and CEO at PowerToFly.com
• Mark Swarek, Artist & Lecturer on Integrated Digital Media

* Food and drinks will be served
* NYU community only (Alumni, Faculty, Staff, Students)
* ID required. Age limit > 21 

When
Friday, April 22, 2016 from 6:00 PM to 8:00 PM (EDT) – Add to Calendar

Where
Leslie eLab – 16 Washington Pl., New York, NY 10003 – View Map

Click here to attend: RSVP

Hot off the press: SONYC is an NYC BigApps finalist! Two weeks ago we pitched the SONYC project at the BigApps semifinals. The results have just been announced, and we’re excited to report that SONYC has made it to the BigApps finals in the Connected Cities category!

​The event will take place on December 2nd at the Brooklyn Academy of Music (BAM). Each team will pitch their project in front of a panel of judges, and there will also be time for Q&A and demos. The event will close with the BigApps Award Ceremony, during which the winner in each category will be announced.

To learn more about the SONYC project have a look at the video below. For a list of academic publications please see our publications page.

The SONYC project has made it to the NYC BigApps semifinals in the Connected Cities Challenge category. Join us for the Demo Day on November 1st to hear the SONYC project pitch, see the demo, and hopefully see us make it into the finals!

What: BigApps Demo Day

When: 12:00PM – 5:00PM  |  Sunday, November 1, 2015

Where: Made in NY Media Center  |  30 John Street  |  Brooklyn, NY 11201

Check out our new video describing the SONYC project!

Our paper “Feature Learning with Deep Scattering for Urban Sound Analysis” has been accepted for publication at the 2015 European Signal Processing Conference.

In this paper we evaluate the scattering transform as an alternative signal representation to the mel-spectrogram in the context of unsupervised feature learning for urban sound classification. We show that we can obtain comparable (or better) performance using the scattering transform whilst reducing both the amount of training data required for feature learning and the size of the learned codebook by an order of magnitude. In both cases the improvement is attributed to the local phase invariance of the representation. We also observe improved classification of sources in the background of the auditory scene, a result that provides further support for the importance of temporal modulation in sound segregation.

The full paper is available on the Publications page.

Our paper “Unsupervised Feature Learning for Urban Sound Classification” has been accepted for publication at the 2015 International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Recent studies have demonstrated the potential of unsupervised feature learning for sound classification. In this paper we further explore the application of the spherical k-means algorithm for feature learning from audio signals, here in the domain of urban sound classification. Spherical k-means is a relatively simple technique that has recently been shown to be competitive with other more complex and time consuming approaches. We study how different parts of the processing pipeline influence performance, taking into account the specificities of the urban sonic environment. We evaluate our approach on the largest public dataset of urban sound sources available for research, and compare it to a baseline system based on MFCCs. We show that feature learning can outperform the baseline approach by configuring it to capture the temporal dynamics of urban sources. The results are complemented with error analysis and some proposals for future research.

The full paper is available on the Publications page.

Our paper “A Dataset and Taxonomy for Urban Sound Research” has been accepted for publication at the 22nd ACM International Conference on Multimedia (ACM-MM’14).

Automatic urban sound classification is a growing area of research with applications in multimedia retrieval and urban informatics. In this paper we identify two main barriers to research in this area – the lack of a common taxonomy and the scarceness of large, real-world, annotated data. To address these issues we present a taxonomy of urban sounds and a new dataset, UrbanSound, containing 27 hours of au- dio with 18.5 hours of annotated sound event occurrences across 10 sound classes. The challenges presented by the new dataset are studied through a series of experiments using a baseline classification system.

The full paper is available on the Publications page. You may also wish to visit the UrbanSound dataset companion website.

Last weekend SONYC researchers Charlie Mydlarz and Justin Salamon participated in the Science in the City hackday which took place as part of the NYC 2014 World Science Festival. Their project, a web-app for crowdsourcing urban sound tagging, won the “Best Social Impact” award.