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Associate Technical EditorsDurand Begaultspatial perception and processing

Eddy Bøgh Brixenaudio forensics

Elizabeth Cohenaudio archiving, storage, and restoration

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Christof Fallerlow bit-rate audio coding

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Robert B. Schuleinmicrophones

Thomas Sporerpsychoacoustics, perception, and listening tests

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Copyright © 2011 Audio Engineering Society, Inc.

Library of Congress Catalog Card No. 88-650002

ISBN 978-0-937803-81-3

First printing July 2011. Printed in the United States of America.

For purposes of review or as citation of authority, brief passages may be reproduced from The Proceedings of theAES 42nd International Conference with customary credit to the source. For other purposes, reproduction of anymaterial in The Proceedings of the AES 42nd International Conference requires the permission of the AudioEngineering Society and the author(s). Inquiries should be sent to: Editorial Office, Audio Engineering Society, Inc.,60 East 42nd Street, New York, New York 10165-2520, USA. Telephone: +1 212 661 8528, Fax: +1 212 682 0477.

The Audio Engineering Society is not responsible for statements made by the contributors.

The papers published in these proceedings have been reproduced from the authors’ manuscripts and withoutconsideration by the Journal Review Board.

AES 42nd INTERNATIONALCONFERENCE

SEMANTIC AUDIO2011 July 22–24

COCHAIRSKarlheinz Brandenburg and Mark Sandler

PAPERS COCHAIRSAnssi Klapuri and Christian Dittmar

TREASURERSylvia Dietrich

SECRETARYPeggy Walther

FACILITIES/EXHIBITORSHolger Großmann

WEBMASTERPeggy Walther

MUSIC INFORMATION RETRIEVAL—PART 1......................................................................9

1-1 [Invited Paper] New Developments in Music Information Retrieval...............................11 Meinard Müller, Saarland University and MPI Informatik, Saarbrücken, Germany

1-2 [Invited Paper] Music Listening in the Future: Augmented Music-Understanding Interfaces and Crowd Music Listening..............................................................................21 Masataka Goto, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

1-3 [Invited Paper] Lost in Translation: Transferring Semantic Audio Analysis from the Lab to Industry....................................................................oral presentation only Jay LeBoef, Imagine Research Inc., San Francisco, CA, USA

POSTER SESSION 1..............................................................................................................31

P1-1 Improving a Multiple Pitch Estimation Method with AR Models ...................................33 Tiago Fernandes Taveres, Jayme Garcia Arnal Barbedo, Amauri Lopes, University of Campinas, Campinas, SP, Brazil

P1-2 Polyphonic Music Transcription Using Weighted CQT and Non-Negative Matrix Factorization ..................................................................................................39 Sang Ha Park, Seokjin Lee, Koeng-Mo Sung, Seoul National University, Kwanak-gu, Seoul, Korea

P1-3 Automatic Classification of Musical Pieces into Global Cultural Areas..........................44 Anna Kruspe, Hanna Lukashevich, Jakob Abeßer, Holger Großmann, Christian Dittmar, Fraunhofer Institute for Digital Media Technology IDMT, Ilmenau, Germany

P1-4 Toward Context-Sensitive Music Recommendations Using Multifaceted User Profiles .................................................................................................................................54 Rafael Schirru, Andreas Dengel, German Research Center for Artificial Intelligence, Kaiserslautern, Germany and University of Kaiserslautern, Kaiserslautern, Germany; Stephan Baumann, German Research Center for Artificial Intelligence, Kaiserslautern, Germany; Christian Freye, Brandenburg University of Applied Sciences, Brandenburg, Germany

P1-5 Regression-Based Tempo Recognition from Chroma and Energy Accents for Slow Audio Recordings ..................................................................................................................60 Thorsten Deinert, Igor Vatolkin, Günter Rudolph, TU Dortmung, Dortmund, Germany

P1-6 Blind Estimation of Reverberation Time from Monophonic Instrument Recordings Based on Non-Negative Matrix Factorization ....................................................................69 Maximo Cobos, Jose J. Lopez, Universitat Politecnica de Valencia, Valencia, Spain; Pedro Vera- Candeas, Julio Jose Carabias-Orti, Nicolas Ruiz-Reyes, Universidad de Jaen, Linares, Spain

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COMMITTEE’S GREETING.................................................................................................7

P1-7 Observing Uncertainty in Music Tagging by Automatic Gaze Tracking ............................79 Bozena Kostek, Gdansk University of Technology, Gdansk, Poland

SPEECH PROCESSING AND ANALYSIS ........................................................................87

2-1 [Invited Paper] Semantic Speech Tagging: Toward Combined Analysis of Speaker Traits....................................................................................................................89 Björn Schuller, Martin Wöllmer, Florian Eyben, Gerhard Rigoll, Technische Universität München, Munich, Germany; Dejan Arsic, Müller-BBM Vibroakustiksysteme, Planegg, Germany

2-2 SyncTS: Automatic Synchronization of Speech and Text Documents ..............................98 David Damm, Harald Grohganz, Sebastian Ewert, Michael Clausen, University of Bonn, Bonn, Germany; Frank Kurth, Fraunhofer Institute for Communication, Information Processing and Ergonomics (FKIE), Wachtberg, Germany

2-3 Extraction of Spectro-Temporal Speech Cues for Robust Automatic Speech Recognition .....................................................................................................................................108 Bernd T. Meyer, International Computer Science Institute (ICSI), Berkeley, CA, USA

AUTOMATIC MUSIC TRANSCRIPTION ..............................................................................119

3-1 Automatic Recognition and Parametrization of Frequency Modulation Techniques in Bass Guitar Recordings ..................................................................................................121 Jakob Abeßer, Christian Dittmar, Fraunhofer Institute for Digital Media Technology, IDMT, Ilmenau Germany; Gerald Schuller, Ilmenau University of Technology, Ilmenau, Germany

3-2 Note Clustering Based on 2-D Source-Filter Modeling for Underdetermined Blind Source Separation ...............................................................................................................129 Martin Spiertz, Volker Gnann, RWTH Aachen University, Aachen, Germany

3-3 Pitch Estimation by the Pair-Wise Evaluation of Spectral Peaks ...................................137 Karin Dressler, Fraunhofer Institute for Digital Media Technology, IDMT, Ilmenau Germany

INFORMED SOURCE SEPARATION......................................................................................147

4-1 [Invited Paper] Parametric Coding of Audio Objects: Technology, Performance and Opportunities ...............................................................................................................149 Jürgen Herre, International Audio Laboratories Erlangen (a joint institution of Fraunhofer IIS and University of Erlangen-Nürnberg), Erlangen, Germany; Leon Terentiv, Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany

4-2 Informed Audio Source Separation from Compressed Linear Stereo Mixtures ...........159 Laurent Girin, Jonathan Pinel, Grenoble Laboratory of Images, Speech, Signal and Automation (GIPSA-lab), Grenoble, France

4-3 Compressive Sensing for Mudic Signals: Comparison of Transforms with Coherent Dictionaries.................................................................................................169 Ch. Srikanth Raj, T. V. Sreenivas, Indian Institute of Science, Bangalor, India

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4-4 “Sparsification” of Audio Signals Using the MDCT/IntMDCT and a Psychoacoustic Model—Application to Informed Audio Source Separation ...........................................179 Jonathan Pinel, Laurent Girin, Grenoble Laboratory of Images, Speech, Signal and Automation (GIPSA-lab), Grenoble, France

POSTER SESSION 2.....................................................................................................................189

P2-1 A Psychoacoustic Approach to Wave Field Synthesis ......................................................191 Tim Ziemer, University of Hamburg, Hamburg, Germany

P2-2 Comparative Evaluation and Combination of Audio Tempo Estimation Approaches .......198 Jose R. Zapata and Emilia Gómez, Universitat Pompeu Fabra, Barcelona, Spain

P2-3 Tempo Estimation from Urban Music Using Non-Negative Matrix Factorization .......208 Daniel Gärtner, Fraunhofer Institute for Digital Media Technology IDMT, Ilmenau, Germany

P2-4 A Musical Source Separation System Using a Source-Filter Model and Beta-Divergence Non-Negative Matrix Factorization .....................................................................................216 Seokjin Lee, SangHa Park, Koeng-Mo Sung, Seoul National University, Kwanak-gu, Seoul, Korea

P2-5 Design of a Karaoke System for Commercial Stereophonic Audio Tracks Aiming a Musical Learning Aid for Amateur Singers ...................................................................221 Karthik. R, Jeyasingh Pathrose, Jasmin Infotech Pvt. Ltd., Chennai, India; M. Madheswaran, Muthayammal Enginering College, Rasipuram, India

P2-6 Geometric Source Separation Method of Audio Signals Based on Beamforming and NMFs .............................................................................................................................228 Seokjin Lee, Sang Ha Park, Koeng-Mo Sung, Seoul National University, Kwanak-gu, Seoul, Korea

AUDIO SOURCE SEPARATION......................................................................................237

5-1 Singing Voice Separation from Stereo Recordings Using Spatial Clues and Robust F0 Estimation.......................................................................................................................239 Pablo Cabañas-Molero, Damián Martínez-Muñoz, University of Jaen, Linares Jaén, Spain; Maximo Cobos, José J. López, Technical University of Valencia, Valencia, Spain

5-2 Influence of Phase, Magnitude and Location of Harmonic Components in the Perceived Quality of Extracted Solo Signals ..........................................................247 Estefanía Cano, Christian Dittmar, Gerald Schuller, Fraunhofer Institute for Digital Media Technology IDMT, Ilmenau, Germany

MUSIC INFORMATION RETRIEVAL—PART 2...........................................................253

6-1 Expressivity in Musical Timing in Relation to Musical Structure and Interpretation: A Cross-Performance, Audio-Based Approach.................................................................255 Cynthia C. S. Liem, Alan Hanjalic, Delft University of Technology, Delft, The Netherlands; Craig Stuart Sapp, CCRMA/CCARH, Stanford University, Stanford, CA, USA

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6-2 Interactive Classification of Sound Objects for Polyphonic Electro-Acoustic Music Annotation............................................................................................................................265 Sebastien Gulluni, Institut National de l’Audiovisuel, Bry-sur-marne Cedex, France and Telecom ParisTech, Paris, France; Slim Essid, Gaël Richard, Telecom ParisTech, Paris, France; Olivier Buisson, Institut National de l’Audiovisuel, Bry-sur-marne Cedex, France

MUSIC INFORMATION RETRIEVAL—PART 3..................................................................273

7-1 [Invited Paper] Adaptive Distance Measures for Exploration and Structuring of Music Collections ............................................................................................................275 Sebastian Stober, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

7-2 Analyzing Chroma Feature Types for Automated Chord Recognition ..........................285 Nanzhu Jiang, Peter Grosche, Verena Konz, Meinard Müller, Saarland University and MPI Informatik, Saarbrücken, Germany

INTELLIGENT AUDIO EFFECTS ...........................................................................................295

8-1 [Invited Paper] Surround Recording Based on a Coincident Pair of Microphones......297 Christof Faller, ILLUSONIC LLC, St-Sulpice, Switzerland

8-2 A Knowledge Representation Framework for Context-Dependent Audio Processing .305 György Fazekas, Thomas Wilmering, Mark B. Sandler, Queen Mary University of London, London, UK

AUTHORS’ INDEX: ............................................................................................................315

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AES 42nd INTERNATIONAL CONFERENCE 7

Mark SandlerConference cochair

Karlheinz BrandenburgConference cochair

About 10 or 12 years ago, it was becoming clear that the next challenge for audio, andmore specifically music, to meet full on was the challenge of the Internet. Not just infinding ways to deliver MP3s, which was just starting about then, but in many, many

aspects.Since those days, another key technology driver has been the decreasing cost of computing

power, coupled with increasing skill in the art and science of digital signal processing. Thismeant that audio signal processing could get ever more complex, and we scientists and engi-neers started to talk in terms of features: meaningful, medium-level aspects of signals thatcaptured something abstract about the underlying nature of a signal. We were used to spectralfeatures, such as those from the ubiquitous FFT, but the past 10 years has seen more andmore different types of these features introduced, analyzed, criticized, and deployed.

And as the complexity of the features has evolved, it has become possible to compute fea-tures that have ever stronger correspondence with our understanding (as perceivers and cre-ators) of music and other sources of audio. With understanding comes meaning. Essentially,semantic audio is a 21st century technology. The newest technological addition to semanticrepresentations of content (so not just audio and music but also video, still images, and narra-tive) is that of the Semantic Web. It enables the concept of ontology—to capture specificmeaning and relationships between entities in a domain of study—and the technology ofresource description framework (RDF). These are the most powerful new tools of our everdeveloping trade. Together they allow the construction of complex online software applica-tions (like mashups but with principles!) and, most important, they allow reasoning to be per-formed on the representations of the features that the advanced digital signal processing hascaptured from the original audio source. This means it is now perfectly plausible to search ina large database or collection for songs that have very unique features, such as “strong elec-tric guitar in the key of A minor at 100–120 beats per minute containing no more than fourinstruments.”

We are very proud to welcome you to the AES 42nd International Conference on SemanticAudio. The idea for this conference emerged in the AES Technical Committee on SemanticAudio. It would not have been possible without the help of AES headquarters, the AES Con-ference Policy Committee, and especially everybody on the 42nd Conference Committee. Wehope you enjoy fruitful discussions and interactions with everyone attending the conferenceand have time to sample the cultural and outdoor activities of Ilmenau and the mountains ofthe Thuringian forest.

KARLHEINZ BRANDENBURG AND MARK SANDLER

CONFERENCE COCHAIRS

Committee’s Greeting