Deep Machine Listening (Special Session @ EUSIPCO 2020)

Deep Machine Listening

Special Session @ EUSIPCO 2020


Theme and Scope

Nowadays, computational algorithms are largely used to face complex modelling, prediction, and recognition tasks in different research fields. One of these fields is represented by Machine Listening, consisting in audio understanding by machine, which finds applications in communications, entertainment, security, forensics, psychology and health to name but a few. Moreover, Machine Listening can get great benefits from the recent interest and great success of Deep Learning techniques.

The typical methodology adopted in these tasks consists in extracting and manipulating useful information from the audio stream to pilot the execution of automatized services. Such an approach is applied to different kinds of audio signals, from music to speech, from sound to acoustic data. In addition, the importance of obtaining reliable performance by using data recorded in real acoustic ambient, where several unpredictable and corruptive causes (like background noise, reverberation, multiple interferences, and so on) always worsen the algorithm behavior, is a challenge of fundamental importance.

It is indeed of great interest for the scientific community to understand the effectiveness of novel computational algorithms for audio processing operating in these environmental conditions, in the light of all aforementioned aspects. Moreover, the exploitation of end-to-end computational models, to directly handle the acoustic raw data, and of cross-domain approaches, to exploit the information contained in diverse kinds of environmental audio signals, have been recently investigated. The aim of this session is therefore to provide the most recent advances in Deep Machine Listening with a wide range of audio processing tasks and applications in real acoustic environments.



Potential topics include, but are not limited, to:

  • Machine Learning for Speech and Audio Processing
  • Cross-domain Audio Analysis
  • Deep Learning for Audio Applications in Real Acoustic Environments
  • Audio-based Security Systems and Surveillance
  • Speech and Audio Forensic Applications
  • Transfer Learning for Changing Environments
  • End-to-end Audio Processing and learning
  • Meta-Learning of Machine Listening Models
  • Separation and Localization of Real Recorded Audio Sources
  • Computational Acoustic Scene Understanding
  • Computational Methods for Wireless Acoustic Sensor Networks
  • Computational Audio Denoising and Dereverberation
  • Deep-ad-hoc Acoustic Beamforming
  • Context-aware Audio Interfaces
  • Adversarial techniques for Audio-metric learning


Paper submission

Prospective authors may submit their manuscripts through EUSIPCO 2020 submission system. All the submissions will go through peer review. More details on paper submission can be found on

The deadline for full paper submissions is February 21, 2020.



For more information, please contact the Special Session organizers:

Michele Scarpiniti Sapienza University of Rome, Italy
Jen-Tzung Chien National Chiao Tung University, Taiwan
Stefano Squartini Università Politecnica delle Marche, Italy