A planar microphone array for spatial coherence-based source separation

We proposed a spatial coherence-based PSD estimation and source separation technique in [1] using a 32-channel spherical microphone array. While the proposed spherical microphone-based method exhibited a satisfactory performance in separating multiple sound sources in a reverberant environment, the use of a large number of microphones remains an issue for some practical considerations. In this paper, we investigate an alternative array structure to achieve spatial coherence-based source separation using a planar microphone array. This method is particularly useful in separating a limited number of sound sources in a mixed acoustic scene. The simplified array structure we used here can easily be integrated with many commercial acoustical instruments such as smart home devices to achieve better speech enhancements.This work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412

Extraction of exterior field from a mixed sound field for 2D height-invariant sound propagation

Any sound field caused by one or more sound sources takes the form of an interior, exterior or a mixed sound field based on the source locations. The recording and reproduction of interior or exterior sound fields in terms of harmonic decomposition has been extensively studied in the literature, however the challenging task of separating them in a mixed field remains largely unexplored. But in nature, the interior and exterior sound fields often co-exist, hence their isolation can be very useful in many acoustic processes. In this paper, we discuss a method to extract the exterior field from a mixed sound field for 2D height-invariant sound propagation. Such an extraction method can be employed to record a sound field in a noisy or interfered room or to perform dereverberation in a reverberant room where the sound fields due to the source signal and its reflections superimpose each other. We demonstrate two practical uses of the proposed method in the forms of (i) an exterior sound field recording in a mixed wave field and (ii) speech dereverberation in a simulated reverberant roomThis work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412)

Surround by Sound: A Review of Spatial Audio Recording and Reproduction

In this article, a systematic overview of various recording and reproduction techniques for spatial audio is presented. While binaural recording and rendering is designed to resemble the human two-ear auditory system and reproduce sounds specifically for a listener’s two ears, soundfield recording and reproduction using a large number of microphones and loudspeakers replicate an acoustic scene within a region. These two fundamentally different types of techniques are discussed in the paper. A recent popular area, multi-zone reproduction, is also briefly reviewed in the paper. The paper is concluded with a discussion of the current state of the field and open problemsThe authors acknowledge National Natural Science Foundation of China (NSFC) No. 61671380 and Australian Research Council Discovery Scheme DE 150100363

3D sound field analysis using circular higher-order microphone array

This paper proposes the theory and design of circular higher-order microphone arrays for 3D sound field analysis using spherical harmonics. Through employing the spherical harmonic translation theorem, the local spatial sound fields recorded by each higher-order microphone placed in the circular arrays are combined to form the sound field information of a large global spherical region. The proposed design reduces the number of the required sampling points and the geometrical complexity of microphone arrays. We develop a two-step method to calculate sound field coefficients using the proposed array structure, i) analytically combine local sound field coefficients on each circular array and ii) solve for global sound field coefficients using data from the first step. Simulation and experimental results show that the proposed array is capable of acquiring the full 3D sound field information over a relatively large spherical region with decent accuracy and computational simplicity.This work was supported under the Australian Research Councils Discovery Projects funding scheme (project no. DP140103412)

Mode Domain Spatial Active Noise Control Using Sparse Signal Representation

Active noise control (ANC) over a sizeable space requires a large number of reference and error microphones to satisfy the spatial Nyquist sampling criterion, which limits the feasibility of practical realization of such systems. This paper proposes a mode-domain feedforward ANC method to attenuate the noise field over a large space while reducing the number of microphones required. We adopt a sparse reference signal representation to precisely calculate the reference mode coefficients. The proposed system consists of circular reference and error microphone arrays, which capture the reference noise signal and residual error signal, respectively, and a circular loudspeaker array to drive the anti-noise signal. Experimental results indicate that above the spatial Nyquist frequency,our proposed method can perform well compared to a conventional methods. Moreover, the proposed method can even reduce the number of reference microphones while achieving better noise attenuation.Comment: to appear at ICASSP 201

Kernel Interpolation of Incident Sound Field in Region Including Scattering Objects

A method for estimating the incident sound field inside a region containing scattering objects is proposed. The sound field estimation method has various applications, such as spatial audio capturing and spatial active noise control; however, most existing methods do not take into account the presence of scatterers within the target estimation region. Although several techniques exist that employ knowledge or measurements of the properties of the scattering objects, it is usually difficult to obtain them precisely in advance, and their properties may change during the estimation process. Our proposed method is based on the kernel ridge regression of the incident field, with a separation from the scattering field represented by a spherical wave function expansion, thus eliminating the need for prior modeling or measurements of the scatterers. Moreover, we introduce a weighting matrix to induce smoothness of the scattering field in the angular direction, which alleviates the effect of the truncation order of the expansion coefficients on the estimation accuracy. Experimental results indicate that the proposed method achieves a higher level of estimation accuracy than the kernel ridge regression without separation.Comment: Accepted to IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 202

Detection, source location, and analysis of volcano infrasound

Thesis (Ph.D.) University of Alaska Fairbanks, 2017The study of volcano infrasound focuses on low frequency sound from volcanoes, how volcanic processes produce it, and the path it travels from the source to our receivers. In this dissertation we focus on detecting, locating, and analyzing infrasound from a number of different volcanoes using a variety of analysis techniques. These works will help inform future volcano monitoring using infrasound with respect to infrasonic source location, signal characterization, volatile flux estimation, and back-azimuth to source determination. Source location is an important component of the study of volcano infrasound and in its application to volcano monitoring. Semblance is a forward grid search technique and common source location method in infrasound studies as well as seismology. We evaluated the effectiveness of semblance in the presence of significant topographic features for explosions of Sakurajima Volcano, Japan, while taking into account temperature and wind variations. We show that topographic obstacles at Sakurajima cause a semblance source location offset of ~360-420 m to the northeast of the actual source location. In addition, we found despite the consistent offset in source location semblance can still be a useful tool for determining periods of volcanic activity. Infrasonic signal characterization follows signal detection and source location in volcano monitoring in that it informs us of the type of volcanic activity detected. In large volcanic eruptions the lowermost portion of the eruption column is momentum-driven and termed the volcanic jet or gas-thrust zone. This turbulent fluid-flow perturbs the atmosphere and produces a sound similar to that of jet and rocket engines, known as jet noise. We deployed an array of infrasound sensors near an accessible, less hazardous, fumarolic jet at Aso Volcano, Japan as an analogue to large, violent volcanic eruption jets. We recorded volcanic jet noise at 57.6° from vertical, a recording angle not normally feasible in volcanic environments. The fumarolic jet noise was found to have a sustained, low amplitude signal with a spectral peak between 7-10 Hz. From thermal imagery we measure the jet temperature (~260 °C) and estimate the jet diameter (~2.5 m). From the estimated jet diameter, an assumed Strouhal number of 0.19, and the jet noise peak frequency, we estimated the jet velocity to be ~79 - 132 m/s. We used published gas data to then estimate the volatile flux at ~160 - 270 kg/s (14,000 - 23,000 t/d). These estimates are typically difficult to obtain in volcanic environments, but provide valuable information on the eruption. At regional and global length scales we use infrasound arrays to detect signals and determine their source back-azimuths. A ground-coupled airwave (GCA) occurs when an incident acoustic pressure wave encounters the Earth's surface and part of the energy of the wave is transferred to the ground. GCAs are commonly observed from sources such as volcanic eruptions, bolides, meteors, and explosions. They have been observed to have retrograde particle motion. When recorded on collocated seismo-acoustic sensors, the phase between the infrasound and seismic signals is 90°. If the sensors are separated wind noise is usually incoherent and an additional phase is added due to the sensor separation. We utilized the additional phase and the characteristic particle motion to determine a unique back-azimuth solution to an acoustic source. The additional phase will be different depending on the direction from which a wave arrives. Our technique was tested using synthetic seismo-acoustic data from a coupled Earth-atmosphere 3D finite difference code and then applied to two well-constrained datasets: Mount St. Helens, USA, and Mount Pagan, Commonwealth of the Northern Mariana Islands Volcanoes. The results from our method are within ~<1° - 5° of the actual and traditional infrasound array processing determined back-azimuths. Ours is a new method to detect and determine the back-azimuth to infrasonic signals, which will be useful when financial and spatial resources are limited

Three dimensional volcano-acoustic source localization at Karymsky Volcano, Kamchatka, Russia

Thesis (M.S.) University of Alaska Fairbanks, 2013We test two methods of 3-D acoustic source localization on volcanic explosions and small-scale jetting events at Karymsky Volcano, Kamchatka, Russia. Recent infrasound studies have provided evidence that volcanic jets produce low-frequency aerodynamic sound (jet noise) similar to that from man-made jet engines. Man-made jets are known to produce sound through turbulence along the jet axis, but discrimination of sources along the axis of a volcanic jet requires a network of sufficient topographic relief to attain resolution in the vertical dimension. At Karymsky Volcano, the topography of an eroded edifice adjacent to the active cone provided a platform for the atypical deployment of five infrasound sensors with intra-network relief of ~600 m in July 2012. A novel 3-D inverse localization method, srcLoc, is tested and compared against a more common grid-search semblance technique. Simulations using synthetic signals indicate that srcLoc is capable of determining vertical source locations for this network configuration to within �150 m or better. However, srcLoc locations for explosions and jetting at Karymsky Volcano show a persistent overestimation of source elevation and underestimation of sound speed by an average of ~330 m and 25 m/s, respectively. The semblance method is able to produce more realistic source locations by fixing the sound speed to expected values of 335 - 340 m/s. The consistency of location errors for both explosions and jetting activity over a wide range of wind and temperature conditions points to the influence of topography. Explosion waveforms exhibit amplitude relationships and waveform distortion strikingly similar to those theorized by modeling studies of wave diffraction around the crater rim. We suggest delay of signals and apparent elevated source locations are due to altered raypaths and/or crater diffraction effects. Our results suggest the influence of topography in the vent region must be accounted for when attempting 3-D volcano acoustic source localization. Though the data presented here are insufficient to resolve noise sources for these jets, which are much smaller in scale than those of previous volcanic jet noise studies, similar techniques may be successfully applied to large volcanic jets in the future.1. Introduction -- 2. Jet noise -- 2.1. Man-made jet noise -- 2.2. Volcanic jet-noise -- 3. Campaign and data -- 3.1. Karymsky Volcano -- 3.2. Acoustic data -- 4. Localization methods -- 4.1. Localization primer -- 4.2. Inverse locator: srcLoc -- 4.3. Forward locator: semblance -- 5. Results and discussion -- 5.1. srcLoc -- 5.2. Semblance -- 5.3. Discussion of errors -- 6. Conclusions -- Reference

Digital acoustics: processing wave fields in space and time using DSP tools

Systems with hundreds of microphones for acoustic field acquisition, or hundreds of loudspeakers for rendering, have been proposed and built. To analyze, design, and apply such systems requires a framework that allows us to leverage the vast set of tools available in digital signal processing in order to achieve intuitive and efficient algorithms. We thus propose a discrete space-time framework, grounded in classical acoustics, which addresses the discrete nature of the spatial and temporal sampling. In particular, a short-space/time Fourier transform is introduced, which is the natural extension of the localized or short-time Fourier transform. Processing in this intuitive domain allows us to easily devise algorithms for beam-forming, source separation, and multi-channel compression, among other useful tasks. The essential space band-limitedness of the Fourier spectrum is also used to solve the spatial equalization task required for sound field rendering in a region of interest. Examples of applications are show