About: Microphone array is a(n) research topic. Over the lifetime, 5936 publication(s) have been published within this topic receiving 70026 citation(s).
Papers published on a yearly basis
01 Jan 2001
TL;DR: This paper presents a meta-modelling architecture for microphone Array Processing that automates the very labor-intensive and therefore time-heavy and expensive process of manually shaping Microphone Arrays for Speech Input in Automobiles.
Abstract: I. Speech Enhancement.- 1 Constant Directivity Beamforming.- 2 Superdirective Microphone Arrays.- 3 Post-Filtering Techniques.- 4 Spatial Coherence Functions for Differential Microphones in Isotropic Noise Fields.- 5 Robust Adaptive Beamforming.- 6 GSVD-Based Optimal Filtering for Multi-Microphone Speech Enhancement.- 7 Explicit Speech Modeling for Microphone Array Speech Acquisition.- II. Source Localization.- 8 Robust Localization in Reverberant Rooms.- 9 Multi-Source Localization Strategies.- 10 Joint Audio-Video Signal Processing for Object Localization and Tracking.- III. Applications.- 11 Microphone-Array Hearing Aids.- 12 Small Microphone Arrays with Postfilters for Noise and Acoustic Echo Reduction.- 13 Acoustic Echo Cancellation for Beamforming Microphone Arrays.- 14 Optimal and Adaptive Microphone Arrays for Speech Input in Automobiles.- 15 Speech Recognition with Microphone Arrays.- 16 Blind Separation of Acoustic Signals.- IV. Open Problems and Future Directions.- 17 Future Directions for Microphone Arrays.- 18 Future Directions in Microphone Array Processing.
•26 Jun 2003
Abstract: A system and method for teleconferencing and recording of meetings. The system uses a variety of capture devices (a novel 360° camera, a whiteboard camera, a presenter view camera, a remote view camera, and a microphone array) to provide a rich experience for people who want to participate in a meeting from a distance. The system is also combined with speaker clustering, spatial indexing, and time compression to provide a rich experience for people who miss a meeting and want to watch it afterward.
Abstract: The quality of sound pickup in large rooms—such as auditoria, conference rooms, or classrooms—is impaired by reverberation and interfering noise sources. These degradations can be minimized by a transducer system that discriminates against sound arrivals from all directions except for that of the desired source. A two‐dimensional array of microphones can be electronically beam steered to accomplish this directivity. This report gives the theory, design, and implementation of a microprocessor system for automatically steering a two‐dimensional microphone array. The signal‐seeking transducer system is implemented as a dual‐beam, “track‐while‐scan” array. It utilizes signal properties to distinguish between desired speech sources and interfering noise. The complete automatic system has been tested in anechoic and medium‐sized auditorium environments, and its performance is discussed.
••01 Dec 2007
TL;DR: A new version of the classical deconvolution method CLEAN is proposed here: CLEAN-SC, which is based on spatial source coherence, and side lobes can be removed of actually measured beam patterns of measured noise sources.
Abstract: To obtain higher resolution acoustic source plots from microphone array measurements, deconvolution techniques are becoming increasingly popular. Deconvolution algorithms aim at identifying Point Spread Functions (PSF) in source plots, and may therefore fall short when actual beam patterns of measured noise sources are not similar to synthetically obtained PSF's. To overcome this, a new version of the classical deconvolution method CLEAN is proposed here: CLEAN-SC. By this new method, which is based on spatial source coherence, side lobes can be removed of actually measured beam patterns. Essentially, CLEAN-SC iteratively removes the part of the source plot which is spatially coherent with the peak source. A feature of CLEAN-SC is its ability to extract absolute sound power levels from the source plots. The merits of CLEAN-SC were demonstrated using array measurements of airframe noise on a scale model of the Airbus A340 in the 8×6 m2 closed test section of DNW-LLF.
13 May 2002
TL;DR: This paper describes a beamforming microphone array consisting of pressure microphones that are mounted on the surface of a rigid sphere based on a spherical harmonic decomposition of the soundfield that allows a simple and computationally effective, yet flexible beamformer structure.
Abstract: This paper describes a beamforming microphone array consisting of pressure microphones that are mounted on the surface of a rigid sphere. The beamformer is based on a spherical harmonic decomposition of the soundfield. We show that this allows a simple and computationally effective, yet flexible beamformer structure. The look-direction can be steered to any direction in 3-D space without changing the beampattern. In general the number of sensors and their location is quite arbitrary as long as they hold a certain orthogonality constraint that we derived. For a practical example we chose a spherical array with 32 elements. The microphones are located at the center of the faces of a truncated icosahedron. The radius of the sphere is 5 cm. With this setup we can achieve a Directivity Index of 12 dB and higher. The operating frequency range is from 100 Hz to 5 kHz.
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