Abstract:

Current musical improvisation systems generate unidimensional musical sequences by recombining their musical contents. However, considering several dimensions (melody, harmony...) and several temporal levels are difficult issues. In this talk, I will summarize the work of my PhD student Ken Déguernel on the combination of probabilistic approaches with formal language theory in order to address those issues. First, I will present a system able to follow the contextual logic of an improvisation modelled by a factor oracle whilst enriching its musical discourse with multidimensional knowledge represented by interpolated probabilistic models. Then, this work is extended to create another system using a belief propagation algorithm representing the interaction between several musicians, or between several dimensions, in order to generate multidimensional improvisations. Finally, we propose a system able to improvise on a temporal scenario with multi-level information modelled with a hierarchical grammar. We also propose a learning method for the automatic analysis of hierarchical temporal structures. All systems have been evaluated by professional musicians and improvisers during listening sessions.

Bio:

Emmanuel Vincent is a Senior Research Scientist with Inria (Nancy, France). He received the Ph.D. degree in music signal processing from IRCAM (Paris, France) in 2004 and worked as a Research Assistant with the Centre for Digital Music at Queen Mary, University of London (London, U.K.) from 2004 to 2006. His research focuses on statistical machine learning for audio, with application to source localization and separation and noise-robust speech recognition, among others. He is a founder of the series of Signal Separation Evaluation Campaigns (SiSEC) and CHiME Speech Separation and Recognition Challenges.

 

Sound Source Localization in Wireless Acoustic Sensor Networks by Maximo Cobos

Abstract:

With the rapid evolution in the design and manufacture of electronic circuits, wireless nodes that integrate sensors and communication interfaces of different types have become economic resources for the design and deployment of innovative monitoring systems. In this context, wireless sensor networks (WSNs) have spread in fields as diverse as security, industry and systems oriented to care and well-being. When nodes incorporate acoustic transducers and the processing involves the manipulation of acoustic signals, such networks are commonly known as wireless acoustic sensor networks (WASNs). Inference of location information has always been an attractive research problem, where traditional (wired) microphone arrays have been employed to identify the number and location of active sound sources. However, practical limiations such as limited processing power, lack of synchronization and battery life of the nodes restrict the direct application of classical approaches within a WASNs framework. The seminar will cover a brief introduction to this research field, as well as an overview of recent approaches to tackle this problem.

Bio:

Maximo Cobos received the Ph.D. degree in telecommunications from Universitat Politècnica de València in 2009. His Ph.D. dissertation was awarded with the Ericsson Best Thesis Award on Multimedia Environments from the Spanish National Telecommunications Engineering Association (COIT). He completed with honors his Ph.D studies under the University Faculty Training program (FPU) and was awarded with a "Campus of Excellence" post-doctoral fellowship to work at the Institute of Telecommunications and Multimedia Applications (iTEAM). Since 2011 he has been with the Computer Science Department of the Universitat de València, where he is now an Associate Professor. His work is focused on the area of digital signal processing for audio and multimedia applications, where he has published more than 90 technical papers in international journals and conferences. Dr. Cobos is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), a Full Member of the Acoustical Society of America (ASA) and a member of the Audio Signal Processing Technical Committee of the European Acoustics Association (EAA).