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EVERYSOUND SIGNED

Computational Analysis of Everyday Soundscapes

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

EVERYSOUND project word cloud

Explore the words cloud of the EVERYSOUND project. It provides you a very rough idea of what is the project "EVERYSOUND" about.

perceive recognize audio vast producing internationally classification monitoring transmitted speed taxonomy distorted separation tackling animal phones realistic place quantities intelligent uploaded multiple carry captured environments joint searching minute unobtrusively park youtube breaking amount form internet sounds recognition tens videos natural size biological algorithms automatically ground multilayer area networks sound environmental approximate expertise physical hours rural hierarchical simultaneously analyze give descriptions speech individual passing urban acoustic mobile content computational categorize human street car pattern environment geographical source reliably tools easily soundscapes overlapping events accurately cultural music sources social multimedia everysound home robots awarded everyday

Project "EVERYSOUND" data sheet

The following table provides information about the project.

Coordinator	TTY-SAATIO There are not information about this coordinator. Please contact Fabio for more information, thanks.
Coordinator Country	Finland [FI]
Total cost	1˙500˙000 €
EC max contribution	1˙500˙000 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2014-STG
Funding Scheme	ERC-STG
Starting year	2015
Duration (year-month-day)	from 2015-05-01 to 2020-04-30

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	TAMPEREEN KORKEAKOULUSAATIO SR TAMPEREEN KORKEAKOULUSAATIO SR Organization address address: KALEVANTIE 4 city: TAMPERE postcode: 33100 website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	FI (TAMPERE)	coordinator	1˙500˙000.00
2	TTY-SAATIO TTY-SAATIO Organization address address: KORKEAKOULUNKATU 10 city: TAMPERE postcode: 33720 website: www.tut.fi contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	FI (TAMPERE)	coordinator	0.00

Map

Project objective

Sounds carry a large amount of information about our everyday environment and physical events that take place in it. For example, when a car is passing by, one can perceive the approximate size and speed of the car. Sound can easily and unobtrusively be captured e.g. by mobile phones and transmitted further – for example, tens of hours of audio is uploaded to the internet every minute e.g. in the form of YouTube videos. However, today's technology is not able to recognize individual sound sources in realistic soundscapes, where multiple sounds are present, often simultaneously, and distorted by the environment. The ground-breaking objective of EVERYSOUND is to develop computational methods which will automatically provide high-level descriptions of environmental sounds in realistic everyday soundscapes such as street, park, home, etc. This requires developing several novel methods, including joint source separation and robust pattern classification algorithms to reliably recognize multiple overlapping sounds, and a hierarchical multilayer taxonomy to accurately categorize everyday sounds. The methods are based on the applicant's internationally recognized and awarded expertise on source separation and robust pattern recognition in speech and music processing, which will allow now tackling the new and challenging research area of everyday sound recognition. The results of EVERYSOUND will enable searching for multimedia based on its audio content, which is not possible with today's technology. It will allow mobile devices, robots, and intelligent monitoring systems to recognize activities in their environments using acoustic information. Producing automatically descriptions of vast quantities of audio will give new tools for geographical, social, cultural, and biological studies to analyze sounds related to human, animal, and natural activity in urban and rural areas, as well as multimedia in social networks.

Publications

List of publications.
year	authors and title	journal	last update
2018	Gharib, Shayan; Drossos, Konstantinos; Ã‡akir, Emre; Serdyuk, Dmitriy; Virtanen, Tuomas Unsupervised adversarial domain adaptation for acoustic scene classification published pages: , ISSN: , DOI:	Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events 2018 1	2020-03-10
2018	Paul Magron, Konstantinos Drossos, Stylianos Ioannis Mimilakis, Tuomas Virtanen Reducing Interference with Phase Recovery in DNN-based Monaural Singing Voice Separation published pages: 332-336, ISSN: , DOI: 10.21437/interspeech.2018-1845	Interspeech 2018	2020-03-10
2019	Sharath Adavanne, Archontis Politis, Joonas Nikunen, Tuomas Virtanen Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks published pages: 34-48, ISSN: 1932-4553, DOI: 10.1109/JSTSP.2018.2885636	IEEE Journal of Selected Topics in Signal Processing 13/1	2020-03-10
2019	Adavanne, Sharath; Politis, Archontis; Virtanen, Tuomas A multi-room reverberant dataset for sound event localization and detection published pages: , ISSN: , DOI:	Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events 2019 1	2020-03-10
2019	Annamaria Mesaros, Toni Heittola, Tuomas Virtanen Acoustic scene classification in DCASE 2019 Challenge: closed and open set classification and data mismatch setups published pages: , ISSN: , DOI:	Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events 2019	2020-03-10
2017	Miroslav Malik, Sharath Adavanne, Konstantinos Drossos, Tuomas Virtanen, Dasa Ticha, Roman Jarina Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition published pages: , ISSN: , DOI:	Proceedings of the 14th Sound and Music Computing Conference, 2017	2020-03-10
2018	Mesaros, Annamaria; Heittola, Toni; Virtanen, Tuomas A multi-device dataset for urban acoustic scene classification published pages: , ISSN: , DOI:	Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop 1	2020-03-10
2019	Samuel Lipping, Konstantinos Drossos, Tuomas Virtanen Crowdsourcing a Dataset of Audio Captions published pages: , ISSN: , DOI:	Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop	2020-03-10
2019	Sharath Adavanne, Archontis Politis, Tuomas Virtanen Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network published pages: , ISSN: , DOI:	Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events, 2019.	2020-03-10
2019	Hendrik Purwins, Bo Li, Tuomas Virtanen, Jan Schluter, Shuo-Yiin Chang, Tara Sainath Deep Learning for Audio Signal Processing published pages: 206-219, ISSN: 1932-4553, DOI: 10.1109/jstsp.2019.2908700	IEEE Journal of Selected Topics in Signal Processing 13/2	2020-03-10
2019	Annamaria Mesaros, Aleksandr Diment, Benjamin Elizalde, Toni Heittola, Emmanuel Vincent, Bhiksha Raj, Tuomas Virtanen Sound Event Detection in the DCASE 2017 Challenge published pages: 992-1006, ISSN: 2329-9290, DOI: 10.1109/TASLP.2019.2907016	IEEE/ACM Transactions on Audio, Speech, and Language Processing 27/6	2020-03-10
2019	Konstantinos Drossos, Shayan Gharib, Paul Magron, Tuomas Virtanen Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling published pages: , ISSN: , DOI:	Proceedings of Workshop on Detection and Classification of Acoustic Scenes and Events 2019	2020-03-10
2017	Konstantinos Drossos, Stylianos Ioannis Mimilakis, Andreas Floros, Tuomas Virtanen, Gerald Schuller Close Miking Empirical Practice Verification: A Source Separation Approach published pages: , ISSN: , DOI:	In proceedings Audio Engineering Society 142th Convention	2020-03-10
2017	Annamaria Mesaros, Toni Heittola, Aleksandr Diment, Benjamin Elizalde, Ankit Shah, Emmanuel Vincent, Bhiksha Raj, and Tuomas Virtanen DCASE 2017 challenge setup: tasks, datasets and baseline system published pages: , ISSN: , DOI:	Proceedings of the Workshop on Detection and Classification of Sound Scenes and Events	2019-05-28
2018	Toni Heittola, Emre Ã‡akÄ±r, Tuomas Virtanen The Machine Learning Approach for Analysis of Sound Scenes and Events published pages: 13-40, ISSN: , DOI: 10.1007/978-3-319-63450-0_2	Computational Analysis of Sound Scenes and Events	2019-05-27
2016	Tuomas Virtanen, Annamaria Mesaros, Toni Heittola, Mark D. Plumbley, Peter Foster, Emmanouil Benetos, and Mathieu Lagrange. (Eds.) Proceedings of the detection and classification of acoustic scenes and events 2016 workshop (DCASE2016) published pages: , ISSN: , DOI:		2019-05-28
2018	Annamaria Mesaros, Toni Heittola, Dan Ellis Datasets and Evaluation published pages: 147-179, ISSN: , DOI: 10.1007/978-3-319-63450-0_6	Computational Analysis of Sound Scenes and Events	2019-05-27
2017	Sharath Adavanne and Tuomas Virtanen Sound event detection using weakly labeled dataset with stacked convolutional and recurrent neural network published pages: , ISSN: , DOI:	Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017)	2019-05-27
2017	Tuomas Virtanen, Annamaria Mesaros, Toni Heittola, Aleksandr Diment, Emmanuel Vincent, Emmanouil Benetos, and Benjamin Martinez Elizalde. (Eds.) Proceedings of the detection and classification of acoustic scenes and events 2017 workshop (DCASE2017) published pages: , ISSN: , DOI:		2019-05-28
2018	Panu Maijala, Zhao Shuyang, Toni Heittola, Tuomas Virtanen Environmental noise monitoring using source classification in sensors published pages: 258-267, ISSN: 0003-682X, DOI: 10.1016/j.apacoust.2017.08.006	Applied Acoustics 129	2019-05-28
2017	Emre Cakir and Tuomas Virtanen Convolutional Recurrent Neural Networks for Rare Sound Event Detection published pages: , ISSN: , DOI:	Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events 2017 (DCASE 2017)	2019-05-27
2017	Emre Cakir, Giambattista Parascandolo, Toni Heittola, Heikki Huttunen, Tuomas Virtanen Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection published pages: 1291-1303, ISSN: 2329-9290, DOI: 10.1109/taslp.2017.2690575	IEEE/ACM Transactions on Audio, Speech, and Language Processing 25/6	2019-05-27
2018	Annamaria Mesaros, Toni Heittola, Emmanouil Benetos, Peter Foster, Mathieu Lagrange, Tuomas Virtanen, Mark D. Plumbley Detection and Classification of Acoustic Scenes and Events: Outcome of the DCASE 2016 Challenge published pages: 379-393, ISSN: 2329-9290, DOI: 10.1109/taslp.2017.2778423	IEEE/ACM Transactions on Audio, Speech, and Language Processing 26/2	2019-05-28
2016	Annamaria Mesaros, Toni Heittola, Tuomas Virtanen Metrics for Polyphonic Sound Event Detection published pages: , ISSN: 2076-3417, DOI: 10.3390/app6060162	Applied Sciences 6	2019-05-28
2016	Konstantinos Drossos, Maximos Kaliakatsos-Papakostas, Andreas Floros, Tuomas Virtanen On the Impact of The Semantic Content of Sound Events in Emotion Elicitation published pages: 525-532, ISSN: 1549-4950, DOI: 10.17743/jaes.2016.0024	Journal of the Audio Engineering Society 64/7/8	2019-05-28

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "EVERYSOUND" project.

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The information about "EVERYSOUND" are provided by the European Opendata Portal: CORDIS opendata.