DCASE2016 Workshop

Workshop on Detection and Classification of Acoustic Scenes and Events
Technical program
Hours Program
9:00 Registration
9:30 Welcome
9:40 Keynote

Acoustic Scene and Events Recognition: How Similar is it to Speech Recognition and Music Genre Recognition?

Gaël Richard

Télécom ParisTech

10:30 DCASE2016

DCASE challenge: Philosophy, tasks and results

Mark D. Plumbley1, Tuomas Virtanen2

1 University of Surrey, United Kingdom 2 Tampere University of Technology, Finland

11:10 Break
11:10 Coffee
11:30 Presentations
11:30 5 presentations, 15 + 3 min presentations each

Bag-of-Features Acoustic Event Detection for Sensor Networks

Julian Kürby, Rene Grzeszick, Axel Plinge, Gernot A. Fink

TU Dortmund University, Germany

Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording

Benjamin Elizalde1, Anurag Kumar1, Ankit Shah2, Rohan Badlani4, Emmanuel Vincent3, Bhiksha Raj1, Ian Lane1

1Carnegie Mellon University, USA 2National Institute of Technology Karnataka Surathkal 3Inria, France 4Birla Institute of Technology and Science

Fully DNN-Based Multi-Label Regression for Audio Tagging

Yong Xu, Qiang Huang, Wenwu Wang, Philip J. B. Jackson, Mark D. Plumbley

University of Surrey, United Kingdom

Acoustic Event Detection Method Using Semi-Supervised Non-Negative Matrix Factorization with Mixtures of Local Dictionaries

Tatsuya Komatsu, Takahiro Toizumi, Reishi Kondo, Yuzo Senda

NEC Corporation, Japan

DCASE 2016 Acoustic Scene Classification Using Convolutional Neural Networks

Michele Valenti1, Aleksandr Diment2, Giambattista Parascandolo2, Stefano Squartini1, Tuomas Virtanen2

1Marche Polytechnic University, Italy 2Tampere University of Technology, Finland

13:00 Break
13:00 Lunch
14:00 Keynote

Audio Event Recognition: Pathways to Impact

Sacha Krstulović

Audio Analytic

14:40 Posters

Gated Recurrent Networks applied to Acoustic Scene Classification

Matthias Zöhrer, Franz Pernkopf

Graz University of Technology, Austria

Bidirectional LSTM-HMM Hybrid System for Polyphonic Sound Event Detection

Tomoki Hayashi1, Shinji Watanabe2, Tomoki Toda1, Takaaki Hori2, Jonathan Le Roux2, Kazuya Takeda1

1Nagoya University, Japan 2Mitsubishi Electric Research Laboratories, USA

DNN-Based Sound Event Detection with Exemplar-Based Approach for Noise Reduction

Inkyu Choi, Kisoo Kwon, Soo Hyun Bae, Nam Soo Kim

Seoul National University, South Korea

Sound Event Detection in Multichannel Audio Using Spatial and Harmonic Features

Sharath Adavanne, Giambattista Parascandolo, Pasi Pertilä, Toni Heittola, Tuomas Virtanen

Tampere University of Technology, Finland

Synthetic Sound Event Detection based on MFCC

Juana M. Gutiérrez-Arriola, Rubén Fraile, Alexander Camacho, Thibaut Durand, Jaime L. Jarrín, Shirley R. Mendoza

Universidad Politécnica de Madrid, Spain

Hierarchical Learning for DNN-Based Acoustic Scene Classification

Yong Xu, Qiang Huang, Wenwu Wang, Mark D. Plumbley

University of Surrey, United Kingdom

Acoustic Scene Classification: An evaluation of an extremely compact feature representation

Gustavo Sena Mafra1, Ngoc Q. K. Duong2, Alexey Ozerov2, Patrick Perez2

1Universidade Federal de Santa Catarina, Brazil 2Technicolor, France

Estimating traffic noise levels using acoustic monitoring a preliminary study

Gloaguen Jean-Rémy1, Can Arnaud1, Lagrange Mathieu2, Petiot Jean-François2

1Ifsttar - LAE, France 2Irccyn, France

Deep Neural Network Baseline for DCASE Challenge 2016

Qiuqiang Kong, Iwona Sobieraj, Wenwu Wang, Mark Plumbley

Surrey University, United Kingdom

Performance comparison of GMM, HMM and DNN based approaches for acoustic event detection within Task 3 of the DCASE 2016 challenge

Jens Schröder1, Jörn Anemüller2, Stefan Goetze1

1Fraunhofer IDMT, Germany 2University of Oldenburg, Germany

Acoustic Scene Classification using Time-Delay Neural Networks and Amplitude Modulation Filter Bank Features

Niko Moritz1,3, Jens Schröder1,3, Stefan Goetze1,3, Jörn Anemüller2,3, Birger Kollmeier1,2,3

1Fraunhofer IDMT-HSA, Germany 2University of Oldenburg, Germany 3Cluster of Excellence "Hearing4all", Germany

CQT-based Convolutional Neural Networks for Audio Scene Classification

Thomas Lidy1, Alexander Schindler2

1Vienna University of Technology, Austria 2Austrian Institute of Technology, Austria

A Real-Time Environmental Sound Recognition System for the Android OS

Angelos Pillos1, Khalid Alghamidi1, Nora Alzamel1, Veselin Pavlov1, Swetha Machanavajhala2

1University College London, United Kingdom 2Microsoft Corp, USA

Coupled Sparse NMF vs. Random Forest Classification for Real Life Acoustic Event Detection

Iwona Sobieraj, Mark D. Plumbley

University of Surrey, United Kingdom

Acoustic Scene Classification Using Parallel Combination of LSTM and CNN

Soo Hyun Bae, Inkyu Choi, Nam Soo Kim

Seoul National University, South Korea

Pairwise Decomposition with Deep Neural Networks and Multiscale Kernel Subspace Learning for Acoustic Scene Classification

Erik Marchi1,3, Dario Tonelli2, Xinzhou Xu1, Fabien Ringeval1,3, Jun Deng1, Stefano Squartini2, Bjoern Schuller1,3,4

1University of Passau, Germany 2Universita Politecnica delle Marche, Italy 3audEERING GmbH, Germany 4Imperial College London, United Kingdom

Improved Dictionary Selection and Detection Schemes in Sparse-CNMF-Based Overlapping Acoustic Event Detection

Panagiotis Giannoulis1,3, Gerasimos Potamianos2,3, Petros Maragos1,3, Athanasios Katsamanis1,3

1National Technical University of Athens, Greece 2University of Thessaly, Greece 3Athena Research and Innovation Center, Greece

DCASE2016 Challenge Results

Annamaria Mesaros1, Toni Heittola1, Tuomas Virtanen1, Emmanouil Benetos2, Mathieu Lagrange3, Grégoire Lafay3, Peter Foster2, Mark D. Plumbley4

1Tampere University of Technology, Finland 2Queen Mary University of London, United Kingdom 3IRCCYN, France 4University of Surrey, United Kingdom

15:30 Coffee
16:10 Panel discussion

Gaël Richard1, Sacha Krstulović2, Jürgen Geiger3, and Stefan Goetze4

1 Télécom ParisTech, France 2 Audio Analytic 3 Huawei Technologies 4 Fraunhofer IDMT

Moderator: Mark Plumbley

16:50 Closing remarks
Social program
Discussions can continue with dinner and drinks (own expense, restaurant nearby)