Computational Analysis of Sound Scenes and Events

Introduction to sound scene and event analysis.- The Machine Learning Approach for Analysis of Sound Scenes and Events.- Acoustics and psychacoustics of sound scenes and events.- Acoustic features for environmental sound analysis.- Statistical Methods for Scene and Event Classification.- Datasets and evaluation.- Everyday Sound Categorization.- Approaches to complex sound scene analysis.- Multiview approaches to event detection and scene analysis.- Sound sharing and retrieval.- Computational bioacoustic scene analysis.- Audio Event Recognition in the Smart Home.- Sound Analysis in Smart Cities.- Future Perspective.- Index.

Tuomas Virtanen is Professor at Laboratory of Signal Processing, Tampere University of Technology (TUT), Finland, where he is leading the Audio Research Group. He received the M.Sc. and Doctor of Science degrees in information technology from TUT in 2001 and 2006, respectively. He has also been working as a research associate at Cambridge University Engineering Department, UK. He is known for his pioneering work on single-channel sound source separation using non-negative matrix factorization based techniques, and their application to noise-robust speech recognition, music content analysis and audio event detection. In addition to the above topics, his research interests include content analysis of audio signals in general and machine learning. He has authored more than 100 scientific publications on the above topics, which have been cited more than 5000 times. He has received the IEEE Signal Processing Society 2012 best paper award for his article "Monaural Sound Source Separation by Nonnegative Matrix Factorization with Temporal Continuity and Sparseness Criteria" as well as three other best paper awards. He is an IEEE Senior Member, a member of the Audio and Acoustic Signal Processing Technical Committee of IEEE Signal Processing Society, Associate Editor of IEEE/ACM Transaction on Audio, Speech, and Language Processing and recipient of the ERC 2014 Starting Grant.

Mark Plumbley is Professor of Signal Processing at the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey, in Guildford, UK. After receiving his Ph.D. degree in neural networks in 1991, he became a Lecturer at King's College London, before moving to Queen Mary University of London in 2002. He subsequently became Professor and Director of the Centre for Digital Music, before joining the University of Surrey in 2015. He is known for his work on analysis and processing of audio and music, using a wide range of signal processing techniques,