EURASIP Journal on Advances in Signal Processing Microphone Array Speech Processing Guest Editors: Sven Nordholm, Thushara Abhayapala, Simon Doclo, Sharon Gannot, Patrick Naylor, and Ivan Tashev Microphone Array Speech Processing EURASIP Journal on Advances in Signal Processing Microphone Array Speech Processing Guest Editors: Sven Nordholm, Thushara Abhayapala, Simon Doclo, Sharon Gannot, Patrick Naylor, and Ivan Tashev Copyright © 2010 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in volume 2010 of “EURASIP Journal on Advances in Signal Processing.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editor-in-Chief Phillip Regalia, Institut National des Tel´ ecommunications,´ France Associate Editors Adel M. Alimi, Tunisia Sudharman K. Jayaweera, USA Douglas O’Shaughnessy, Canada Kenneth Barner, USA Soren Holdt Jensen, Denmark Bjorn¨ Ottersten, Sweden Yasar Becerikli, Turkey Mark Kahrs, USA Jacques Palicot, France Kostas Berberidis, Greece Moon Gi Kang, South Korea Ana Perez-Neira, Spain Enrico Capobianco, Italy Walter Kellermann, Germany Wilfried R. Philips, Belgium A. Enis Cetin, Turkey Lisimachos P. Kondi, Greece Aggelos Pikrakis, Greece Jonathon Chambers, UK Alex Chichung Kot, Singapore Ioannis Psaromiligkos, Canada Mei-Juan Chen, Taiwan Ercan E. Kuruoglu, Italy Athanasios Rontogiannis, Greece Liang-Gee Chen, Taiwan Tan Lee, China Gregor Rozinaj, Slovakia Satya Dharanipragada, USA Geert Leus, The Netherlands Markus Rupp, Austria Kutluyil Dogancay, Australia T.-H. Li, USA William Sandham, UK Florent Dupont, France Husheng Li, USA B. Sankur, Turkey Frank Ehlers, Italy Mark Liao, Taiwan Erchin Serpedin, USA Sharon Gannot, Israel Y.-P. Lin, Taiwan Ling Shao, UK Samanwoy Ghosh-Dastidar, USA Shoji Makino, Japan Dirk Slock, France Norbert Goertz, Austria Stephen Marshall, UK Yap-Peng Tan, Singapore M. Greco, Italy C. Mecklenbrauker,¨ Austria Joao˜ Manuel R. S. Tavares, Portugal IreneY.H.Gu,Sweden Gloria Menegaz, Italy George S. Tombras, Greece Fredrik Gustafsson, Sweden Ricardo Merched, Brazil Dimitrios Tzovaras, Greece Ulrich Heute, Germany Marc Moonen, Belgium Bernhard Wess, Austria Sangjin Hong, USA Christophoros Nikou, Greece Jar-Ferr Yang, Taiwan Jiri Jan, Czech Republic Sven Nordholm, Australia Azzedine Zerguine, Saudi Arabia Magnus Jansson, Sweden Patrick Oonincx, The Netherlands Abdelhak M. Zoubir, Germany Contents Microphone Array Speech Processing, Sven Nordholm, Thushara Abhayapala, Simon Doclo, Sharon Gannot (EURASIPMember), Patrick Naylor, and Ivan Tashev Volume 2010, Article ID 694216, 3 pages Selective Frequency Invariant Uniform Circular Broadband Beamformer,XinZhang,WeeSer, Zhang Zhang, and Anoop Kumar Krishna Volume 2010, Article ID 678306, 11 pages First-Order Adaptive Azimuthal Null-Steering for the Suppression of Two Directional Interferers, ReneM.M.Derkx´ Volume 2010, Article ID 230864, 16 pages Musical-Noise Analysis in Methods of Integrating Microphone Array and Spectral Subtraction Based on Higher-Order Statistics, Yu Takahashi, Hiroshi Saruwatari, Kiyohiro Shikano, and Kazunobu Kondo Volume 2010, Article ID 431347, 25 pages Microphone Diversity Combining for In-Car Applications,Jurgen¨ Freudenberger, Sebastian Stenzel, and Benjamin Venditti Volume 2010, Article ID 509541, 13 pages DOA Estimation with Local-Peak-Weighted CSP, Osamu Ichikawa, Takashi Fukuda, and Masafumi Nishimura Volume 2010, Article ID 358729, 9 pages Shooter Localization in Wireless Microphone Networks, David Lindgren, Olof Wilsson, Fredrik Gustafsson, and Hans Habberstad Volume 2010, Article ID 690732, 11 pages Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010, Article ID 694216, 3 pages doi:10.1155/2010/694216 Editorial Microphone Array Speech Processing Sven Nordholm (EURASIP Member),1 Thushara Abhayapala (EURASIP Member),2 Simon Doclo (EURASIP Member),3 Sharon Gannot (EURASIP Member),4 Patrick Naylor (EURASIP Member),5 and Ivan Tashev6 1 Department of Electrical and Computer Engineering, Curtin University of Technology, Perth, WA 6845, Australia 2 College of Engineering & Computer Science, The Australian National University, Canberra, ACT 0200, Australia 3 Institute of Physics, Signal Processing Group, University of Oldenburg, 26111 Oldenburg, Germany 4 School of Engineering, Bar-Ilan University, 52900 Tel Aviv, Israel 5 Department of Electrical and Electronic Engineering, Imperial College, London SW7 2AZ, UK 6 Microsoft Research, USA Correspondence should be addressed to Sven Nordholm, [email protected] Received 21 July 2010; Accepted 21 July 2010 Copyright © 2010 Sven Nordholm et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Significant knowledge about microphone arrays has been highly reverberant speech given that we only can observe the gained from years of intense research and product develop- received microphone signals. ment. There have been numerous applications suggested, for This special issue contains contributions to traditional example, from large arrays (in the order of >100 elements) areas of research such as frequency invariant beamforming for use in auditoriums to small arrays with only 2 or 3 [1], hand-free operation of microphone arrays in cars [2], elements for hearing aids and mobile telephones. Apart from and source localisation [3]. The contributions show new that, microphone array technology has been widely applied ways to study these traditional problems and give new in speech recognition, surveillance, and warfare. Traditional insights into those problems. Small size arrays have always techniques that have been used for microphone arrays a lot of applications and interest for mobile terminals, include fixed spatial filters, such as, frequency invariant hearing aids, and close up microphones [4]. The novel beamformers, optimal and adaptive beamformers. These way to represent small size arrays leads to a capability to array techniques assume either model knowledge or cali- suppress multiple interferers. Abnormalities in noise and bration signal knowledge as well as localization information speech stemming from processing are largely unavoidable, for their design. Thus they usually combine some form and using nonlinear processing results often in significant of localisation and tracking with the beamforming. Today character change particularly in noise character. It is thus contemporary techniques using blind signal separation (BSS) important to provide new insights into those phenomena and time frequency masking technique have attracted sig- particularly the so called musical noise [5]. Finally, new nificant attention. Those techniques are less reliant on array and unusual use of microphone arrays is always interesting model and localization, but more on the statistical properties to see. Distributed microphone arrays in a sensor network of speech signals such as sparseness, non-Gaussianity, and [6] provide a novel approach to find snipers. This type of non-stationarity. The main advantage that multiple micro- processing has good opportunities to grow in interest for new phones add from a theoretical perspective is the spatial and improved applications. diversity, which is an effective tool to combat interference, The contributions found in this special issue can be reverberation, and noise. The underpinning physical feature categorized to three main aspects of microphone array used is a difference in coherence in the target field (speech processing: (i) microphone array design based on eigenmode signal) versus the noise field. Viewing the processing in this decomposition [1, 4]; (ii) multichannel processing methods way one can understand also the difficulty in enhancing [2, 5]; and (iii) source localisation [3, 6]. 2 EURASIP Journal on Advances in Signal Processing The paper by Zhang et al., “Selective frequency invariant array signal processing and spectral subtraction. To obtain uniform circular broadband beamformer”[1], describes a better noise reduction, methods of integrating microphone design method for Frequency-Invariant (FI) beamforming. array signal processing and nonlinear signal processing have This problem is a well-known array signal processing tech- been researched. However, nonlinear signal processing often nique used in many applications such as, speech acquisition, generates musical noise. Since such musical noise causes acoustic imaging and communications purposes. However, discomfort to users, it is desirable that musical noise is many existing FI beamformers are designed to have a mitigated. Moreover, it has been recently reported that frequency invariant gain over all angles. This might not be higher-order statistics are strongly related to the amount necessary and if a gain constraint is confined to a specific of musical noise generated. This implies that it is possible angle, then the FI performance over that selected region (in to optimize the integration method from the viewpoint of frequency and angle) can be expected to improve. Inspired not only noise reduction performance but also the amount by this idea, the proposed algorithm attempts to optimize of musical noise generated. Thus, the simplest methods the frequency invariant beampattern solely for the mainlobe