非球形のアレイ形状を持つAmbisonicsの定式化

Tohoku University鈴木陽一課

Spatial dissection of a soundfield using spherical harmonic decomposition

A real-world soundfield is often contributed by multiple desired and undesired sound sources. The performance of many acoustic systems such as automatic speech recognition, audio surveillance, and teleconference relies on its ability to extract the desired sound components in such a mixed environment. The existing solutions to the above problem are constrained by various fundamental limitations and require to enforce different priors depending on the acoustic condition such as reverberation and spatial distribution of sound sources. With the growing emphasis and integration of audio applications in diverse technologies such as smart home and virtual reality appliances, it is imperative to advance the source separation technology in order to overcome the limitations of the traditional approaches. To that end, we exploit the harmonic decomposition model to dissect a mixed soundfield into its underlying desired and undesired components based on source and signal characteristics. By analysing the spatial projection of a soundfield, we achieve multiple outcomes such as (i) soundfield separation with respect to distinct source regions, (ii) source separation in a mixed soundfield using modal coherence model, and (iii) direction of arrival (DOA) estimation of multiple overlapping sound sources through pattern recognition of the modal coherence of a soundfield. We first employ an array of higher order microphones for soundfield separation in order to reduce hardware requirement and implementation complexity. Subsequently, we develop novel mathematical models for modal coherence of noisy and reverberant soundfields that facilitate convenient ways for estimating DOA and power spectral densities leading to robust source separation algorithms. The modal domain approach to the soundfield/source separation allows us to circumvent several practical limitations of the existing techniques and enhance the performance and robustness of the system. The proposed methods are presented with several practical applications and performance evaluations using simulated and real-life dataset

Advancing-side directivity and retreating-side interactions of model rotor blade-vortex interaction noise

Acoustic data are presented from a 40 percent scale model of the four-bladed BO-105 helicopter main rotor, tested in a large aerodynamic wind tunnel. Rotor blade-vortex interaction (BVI) noise data in the low-speed flight range were acquired using a traversing in-flow microphone array. Acoustic results presented are used to assess the acoustic far field of BVI noise, to map the directivity and temporal characteristics of BVI impulsive noise, and to show the existence of retreating-side BVI signals. The characterics of the acoustic radiation patterns, which can often be strongly focused, are found to be very dependent on rotor operating condition. The acoustic signals exhibit multiple blade-vortex interactions per blade with broad impulsive content at lower speeds, while at higher speeds, they exhibit fewer interactions per blade, with much sharper, higher amplitude acoustic signals. Moderate-amplitude BVI acoustic signals measured under the aft retreating quadrant of the rotor are shown to originate from the retreating side of the rotor

Robustness and Distance Discrimination of Adaptive Near Field Beamformers

A robust adaptive beamformer is proposed using the near field regionally constrained adaptive approach that designs a set of linear constraints by filtering on a low rank subspace of the near field signal over a spatial region and a wide frequency band. This method can accurately control the beam-former response over the designed spatial-temporal region using a small number of linear constraint vectors and improve the robustness against target location errors. Meanwhile, this method enhances the capability of the near field beamformer in distance discrimination without additional constraints so that interference impinging at the same direction as the desired signal but at a different distance can be effectively suppressed

Robust Near-Field Adaptive Beamforming with Distance Discrimination

This paper proposes a robust near-field adaptive beamformer for microphone array applications in small rooms. Robustness against location errors is crucial for near-field adaptive beamforming due to the difficulty in estimating near-field signal locations especially the radial distances. A near-field regionally constrained adaptive beamformer is proposed to design a set of linear constraints by filtering on a low rank subspace of the near-field signal over a spatial region and frequency band such that the beamformer response over the designed spatial-temporal region can be accurately controlled by a small number of linear constraint vectors. The proposed constraint design method is a systematic approach which guarantees real arithmetic implementation and direct time domain algorithms for broadband beamforming. It improves the robustness against large errors in distance and directions of arrival, and achieves good distance discrimination simultaneously. We show with a nine-element uniform linear array that the proposed near-field adaptive beamformer is robust against distance errors as large as ±32% of the presumed radial distance and angle errors up to ±20⁰. It can suppress a far field interfering signal with the same angle of incidence as a near-field target by more than 20 dB with no loss of the array gain at the near-field target. The significant distance discrimination of the proposed near-field beamformer also helps to improve the dereverberation gain and reduce the desired signal cancellation in reverberant environments

SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field

Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

International audienc

Epälineaarisen signaaliriippuvan akustisen keilanmuodostajan reaaliaikaimplementaatio

A real-time acoustical beamforming system incorporating the cross pattern coherence (CroPaC) post filtering method is implemented in this thesis. The real-time implementation consists of a signal-independent beamformer that is used for spatial discrimination of a sound field. The signal of the beamformer is post filtered by modulating it with a parameter that is derived from the cross-spectrum of two directional microphone signals. The post filter is implemented to enhance performance of beamforming (increase in signal-to-noise ratio), because beamformers are not efficient in environments with high level of reverberation. The post filtering method has been previously implemented in MATLAB for non-real-time use, and this system is the first real-time implementation of an acoustical beamforming system utilizing it. The implementation is programmed in the programming language C for the graphical signal processing program Max developed by Cycling '74. It utilizes a time-frequency domain processing, and the spherical Fourier transform for a decomposition of a sound field into spherical harmonic signals. The implementation can be used with microphone arrays with maximum of 32 microphone capsules, which are laid over rigid sphere with uniform or nearly-uniform arrangements. The real-time implementation can be utilized in many applications, which require algorithm to work in real-time, such as teleconferencing and acoustical cameras.Tässä diplomityössä implementoidaan reaaliaikainen akustinen keilanmuodostusjärjestelmä signaalien väliseen koherenssiin perustuvalla (CroPaC) jälkisuodatuksella. Reaaliaikaimplementaatio koostuu signaaliriippumattomasta keilanmuodostajasta, jota käytetään äänikentän spatiaaliseen suodatukseen. Keilanmuodostajan signaalia jälkisuodatetaan moduloimalla sitä parametrilla, joka johdetaan kahden suuntamikrofonin signaalin välisestä koherenssista. Jälkisuodatus implementoidaan keilanmuodostajan suorituskyvyn parantamiseksi (signaali-kohina-suhteen kasvu), sillä keilanmuodostajat eivät ole tehokkaita kaiuntaisissa ympäristöissä. Jälkisuodatusmetodi on aikaisemmin implementoitu MATLABissa ei-reaaliaikakäyttöä varten. Tämän työn implementaatio on ensimmäinen reaaliaikainen akustinen keilanmuodostusjärjestelmä, joka hyödyntää CroPaC-jälkisuodatusta. Implementaatio on ohjelmoitu C-ohjelmointikielellä graafiselle signaalinprosessointityökalulle Max, jonka on kehittänyt Cycling '74. Prosessointi tapahtuu aika-taajuustasossa ja siinä hyödynnetään äänikentän dekompositiota palloharmonisiin signaaleihin. Implementaatiota voidaan käyttää mikrofoniryhmällä, jossa on korkeintaan 32 mikrofonikapselia, jotka on asetettu jäykän pallon päälle tasavälein tai lähes tasavälein. Reaaliaikaimplementaatiota voidaan hyödyntää lukuisissa sovelluksissa, jotka edellyttävät algoritmin reaaliaikaista toimintaa, esimerkiksi puhelinkokouksissa ja akustisissa kameroissa

Robust Multichannel Microphone Beamforming

In this thesis, a method for the design and implementation of a spatially robust multichannel microphone beamforming system is presented. A set of spatial correlation functions are derived for 2D and 3D far-field/near-field scenarios based on von Mises(-Fisher), Gaussian, and uniform source location distributions. These correlation functions are used to design spatially robust beamformers and blocking beamformers (nullformers) designed to enhance or suppress a known source, where the target source location is not perfectly known due to either an incorrect location estimate or movement of the target while the beamformers are active. The spatially robust beam/null-formers form signal and interferer plus noise references which can be further processed via a blind source separation algorithm to remove mutual components - removing the interference and sensor noise from the signal path and vice versa. The noise reduction performance of the combined beamforming and blind source separation system approaches that of a perfect information MVDR beamformer under reverberant conditions. It is demonstrated that the proposed algorithm can be implemented on low-power hardware with good performance on hardware similar to current mobile platforms using a four-element microphone array