TY - JOUR AB - Today, we are often surrounded by devices with one or more microphones, such as smartphones, laptops, and wireless microphones. If they are part of an acoustic sensor network, their distribution in the environment can be beneficially exploited for various speech processing tasks. However, applications like speaker localization, speaker tracking, and speech enhancement by beamforming avail themselves of the geometrical configuration of the sensors. Therefore, acoustic microphone geometry calibration has recently become a very active field of research. This article provides an application-oriented, comprehensive survey of existing methods for microphone position self-calibration, which will be categorized by the measurements they use and the scenarios they can calibrate. Selected methods will be evaluated comparatively with real-world recordings. AU - Plinge, Axel AU - Jacob, Florian AU - Haeb-Umbach, Reinhold AU - Fink, Gernot A. ID - 11886 IS - 4 JF - IEEE Signal Processing Magazine KW - Acoustic sensors KW - Microphones KW - Portable computers KW - Smart phones KW - Wireless communication KW - Wireless sensor networks SN - 1053-5888 TI - Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms VL - 33 ER - TY - CONF AB - To optimize the ultrasound irradiation for cavitation based ultrasound applications like sonochemistry or ultrasound cleaning, the correlation between cavitation intensity and the resulting effect on the process is of interest. Furthermore, changing conditions like temperature and pressure result in varying acoustic properties of the liquid. That might necessitate an adaption of the ultrasound irradiation. To detect such changes during operation, process monitoring is desired. Labor intensive processes, that might be carried out for several hours, also require process monitoring to increase their reliability by detection of changes or malfunctions during operation. In some applications cavitation detection and monitoring can be achieved by the application of sensors in the sound field. Though the application of sensors is possible, this necessitates modifications on the system and the sensor might disturb the sound field. In other applications harsh, process conditions prohibit the application of sensors in the sound field. Therefore alternative techniques for cavitation detection and monitoring are desired. The applicability of an external microphone and a self-sensing ultrasound transducer for cavitation detection were experimentally investigated. Both methods were found to be suitable and easily applicable. AU - Bornmann, Peter AU - Hemsel, Tobias AU - Sextro, Walter AU - Maeda, Takafumi AU - Morita, Takeshi ID - 9783 KW - cavitation KW - chemical reactors KW - microphones KW - process monitoring KW - reliability KW - ultrasonic applications KW - ultrasonic waves KW - acoustic properties KW - cavitation based ultrasound applications KW - cavitation intensity KW - change detection reliability KW - external microphone KW - malfunction detection reliability KW - nonperturbing cavitation detection KW - nonperturbing cavitation monitoring KW - process monitoring KW - self-sensing ultrasound transducer KW - sonochemical reactors KW - sonochemistry KW - ultrasound cleaning KW - ultrasound irradiation KW - Acoustics KW - Liquids KW - Monitoring KW - Sensors KW - Sonar equipment KW - Transducers KW - Ultrasonic imaging SN - 1948-5719 T2 - Ultrasonics Symposium (IUS), 2012 IEEE International TI - Non-perturbing cavitation detection / monitoring in sonochemical reactors ER - TY - JOUR AB - Maximizing the output signal-to-noise ratio (SNR) of a sensor array in the presence of spatially colored noise leads to a generalized eigenvalue problem. While this approach has extensively been employed in narrowband (antenna) array beamforming, it is typically not used for broadband (microphone) array beamforming due to the uncontrolled amount of speech distortion introduced by a narrowband SNR criterion. In this paper, we show how the distortion of the desired signal can be controlled by a single-channel post-filter, resulting in a performance comparable to the generalized minimum variance distortionless response beamformer, where arbitrary transfer functions relate the source and the microphones. Results are given both for directional and diffuse noise. A novel gradient ascent adaptation algorithm is presented, and its good convergence properties are experimentally revealed by comparison with alternatives from the literature. A key feature of the proposed beamformer is that it operates blindly, i.e., it neither requires knowledge about the array geometry nor an explicit estimation of the transfer functions from source to sensors or the direction-of-arrival. AU - Warsitz, Ernst AU - Haeb-Umbach, Reinhold ID - 11927 IS - 5 JF - IEEE Transactions on Audio, Speech, and Language Processing KW - acoustic signal processing KW - arbitrary transfer function KW - array signal processing KW - blind acoustic beamforming KW - direction-of-arrival KW - direction-of-arrival estimation KW - eigenvalues and eigenfunctions KW - generalized eigenvalue decomposition KW - gradient ascent adaptation algorithm KW - microphone arrays KW - microphones KW - narrowband array beamforming KW - sensor array KW - single-channel post-filter KW - spatially colored noise KW - transfer functions TI - Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition VL - 15 ER - TY - CONF AB - The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method. AU - Warsitz, Ernst AU - Haeb-Umbach, Reinhold ID - 11931 KW - bimodal human-robot interface KW - binaural signal processing KW - enhanced single-channel input signal KW - filter-and-sum beamforming KW - filtering theory KW - FIR filter coefficient KW - generalized cross correlation method KW - microphones KW - microphone signal KW - nonlinear Bayesian tracking KW - particle filtering KW - robust adaptive algorithm KW - robust speaker direction estimation KW - signal processing KW - speech enhancement KW - speech recognition KW - speech recognizer KW - user interfaces T2 - IEEE Workshop on Multimedia Signal Processing (MMSP 2004) TI - Robust speaker direction estimation with particle filtering ER -