Computational Acoustic Scene Analysis

Dear Colleagues,

Computational acoustic scene analysis is a highly-active research field where audio signal processing and machine learning meet several scientific topics, such as room acoustics, microphone arrays, sound source localization, source separation, acoustic event detection, pattern classification, and many others. Emerging application fields include surveillance, environmental monitoring, hearing-aids, distant-speech interaction, for example in smart-home and industry automation. In most of these cases, state-of-the-art techniques are still inadequate for a deployment in real-world contexts.

Indeed, very challenging research problems need to be solved, since real-world noisy and reverberant environments are typically characterized by the presence of multiple speakers and noise sources, often overlapping each other. With the recent advent of machine learning, a significant transformation is under way in these fields, as witnessed by many papers presented in recent conferences, workshops, and even challenges such as DCASE, ACE, REVERB and CHIME.

In this Special Issue, we aim to describe current advances on computational methods on acoustic scene analysis in the following topics, but not limited to them:

• Acoustic event detection and classification

• Acoustic scene classification

• Environmental monitoring by means of audio signals

• Sound source localization and tracking

• Sound source and speech activity detection

• Blind source separation

• Acoustic scene understanding

Preference will be given to works describing advanced digital signal processing and machine learning techniques applied to challenging contexts, such as multiple sources, often overlapping each other, under real-world noisy and reverberant environments.

Dr. Maurizio Omologo
Prof. Dr. Stefano Squartini
Prof. Dr. Tuomas Virtanen
Guest Editors

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