Spherical microphone array acoustic rake receivers

Several signal independent acoustic rake receivers are proposed for speech dereverberation using spherical microphone arrays. The proposed rake designs take advantage of multipaths, by separately capturing and combining early reflections with the direct path. We investigate several approaches in combining reflections with the direct path source signal, including the development of beam patterns that point nulls at all preceding reflections. The proposed designs are tested in experimental simulations and their dereverberation performances evaluated using objective measures. For the tested configuration, the proposed designs achieve higher levels of dereverberation compared to conventional signal independent beamforming systems; achieving up to 3.6 dB improvement in the direct-to-reverberant ratio over the plane-wave decomposition beamformer

Listening to Distances and Hearing Shapes:Inverse Problems in Room Acoustics and Beyond

A central theme of this thesis is using echoes to achieve useful, interesting, and sometimes surprising results. One should have no doubts about the echoes' constructive potential; it is, after all, demonstrated masterfully by Nature. Just think about the bat's intriguing ability to navigate in unknown spaces and hunt for insects by listening to echoes of its calls, or about similar (albeit less well-known) abilities of toothed whales, some birds, shrews, and ultimately people. We show that, perhaps contrary to conventional wisdom, multipath propagation resulting from echoes is our friend. When we think about it the right way, it reveals essential geometric information about the sources--channel--receivers system. The key idea is to think of echoes as being more than just delayed and attenuated peaks in 1D impulse responses; they are actually additional sources with their corresponding 3D locations. This transformation allows us to forget about the abstract \emph{room}, and to replace it by more familiar \emph{point sets}. We can then engage the powerful machinery of Euclidean distance geometry. A problem that always arises is that we do not know \emph{a priori} the matching between the peaks and the points in space, and solving the inverse problem is achieved by \emph{echo sorting}---a tool we developed for learning correct labelings of echoes. This has applications beyond acoustics, whenever one deals with waves and reflections, or more generally, time-of-flight measurements. Equipped with this perspective, we first address the ``Can one hear the shape of a room?'' question, and we answer it with a qualified ``yes''. Even a single impulse response uniquely describes a convex polyhedral room, whereas a more practical algorithm to reconstruct the room's geometry uses only first-order echoes and a few microphones. Next, we show how different problems of localization benefit from echoes. The first one is multiple indoor sound source localization. Assuming the room is known, we show that discretizing the Helmholtz equation yields a system of sparse reconstruction problems linked by the common sparsity pattern. By exploiting the full bandwidth of the sources, we show that it is possible to localize multiple unknown sound sources using only a single microphone. We then look at indoor localization with known pulses from the geometric echo perspective introduced previously. Echo sorting enables localization in non-convex rooms without a line-of-sight path, and localization with a single omni-directional sensor, which is impossible without echoes. A closely related problem is microphone position calibration; we show that echoes can help even without assuming that the room is known. Using echoes, we can localize arbitrary numbers of microphones at unknown locations in an unknown room using only one source at an unknown location---for example a finger snap---and get the room's geometry as a byproduct. Our study of source localization outgrew the initial form factor when we looked at source localization with spherical microphone arrays. Spherical signals appear well beyond spherical microphone arrays; for example, any signal defined on Earth's surface lives on a sphere. This resulted in the first slight departure from the main theme: We develop the theory and algorithms for sampling sparse signals on the sphere using finite rate-of-innovation principles and apply it to various signal processing problems on the sphere

Rake, Peel, Sketch:The Signal Processing Pipeline Revisited

The prototypical signal processing pipeline can be divided into four blocks. Representation of the signal in a basis suitable for processing. Enhancement of the meaningful part of the signal and noise reduction. Estimation of important statistical properties of the signal. Adaptive processing to track and adapt to changes in the signal statistics. This thesis revisits each of these blocks and proposes new algorithms, borrowing ideas from information theory, theoretical computer science, or communications. First, we revisit the Walsh-Hadamard transform (WHT) for the case of a signal sparse in the transformed domain, namely that has only K †N non-zero coefficients. We show that an efficient algorithm exists that can compute these coefficients in O(K log2(K) log2(N/K)) and using only O(K log2(N/K)) samples. This algorithm relies on a fast hashing procedure that computes small linear combinations of transformed domain coefficients. A bipartite graph is formed with linear combinations on one side, and non-zero coefficients on the other. A peeling decoder is then used to recover the non-zero coefficients one by one. A detailed analysis of the algorithm based on error correcting codes over the binary erasure channel is given. The second chapter is about beamforming. Inspired by the rake receiver from wireless communications, we recognize that echoes in a room are an important source of extra signal diversity. We extend several classic beamforming algorithms to take advantage of echoes and also propose new optimal formulations. We explore formulations both in time and frequency domains. We show theoretically and in numerical simulations that the signal-to-interference-and-noise ratio increases proportionally to the number of echoes used. Finally, beyond objective measures, we show that echoes also directly improve speech intelligibility as measured by the perceptual evaluation of speech quality (PESQ) metric. Next, we attack the problem of direction of arrival of acoustic sources, to which we apply a robust finite rate of innovation reconstruction framework. FRIDA â the resulting algorithm â exploits wideband information coherently, works at very low signal-to-noise ratio, and can resolve very close sources. The algorithm can use either raw microphone signals or their cross- correlations. While the former lets us work with correlated sources, the latter creates a quadratic number of measurements that allows to locate many sources with few microphones. Thorough experiments on simulated and recorded data shows that FRIDA compares favorably with the state-of-the-art. We continue by revisiting the classic recursive least squares (RLS) adaptive filter with ideas borrowed from recent results on sketching least squares problems. The exact update of RLS is replaced by a few steps of conjugate gradient descent. We propose then two different precondi- tioners, obtained by sketching the data, to accelerate the convergence of the gradient descent. Experiments on artificial as well as natural signals show that the proposed algorithm has a performance very close to that of RLS at a lower computational burden. The fifth and final chapter is dedicated to the software and hardware tools developed for this thesis. We describe the pyroomacoustics Python package that contains routines for the evaluation of audio processing algorithms and reference implementations of popular algorithms. We then give an overview of the microphone arrays developed

Linear prediction based dereverberation for spherical microphone arrays

Dereverberation is an important preprocessing step in many speech systems, both for human and machine listening. In many situations, including robot audition, the sound sources of interest can be incident from any direction. In such circumstances, a spherical microphone array allows direction of arrival estimation which is free of spatial aliasing and directionindependent beam patterns can be formed. This contribution formulates the Weighted Prediction Error algorithm in the spherical harmonic domain and compares the performance to a space domain implementation. Simulation results demonstrate that performing dereverberation in the spherical harmonic domain allows many more microphones to be used without increasing the computational cost. The benefit of using many microphones is particularly apparent at low signal to noise ratios, where for the conditions tested up to 71% improvement in speech-to-reverberation modulation ratio was achieved

Under-modelled blind system identification for time delay estimation in reverberant environments

In multichannel systems, acoustic time delay estimation (TDE) is a challenging problem in reverberant environments. Although blind system identification (BSI) based methods have been proposed which utilize a realistic signal model for the room impulse response (RIR), their TDE performance depends strongly on that of the BSI, which is often inaccurate in practice when the identified responses are under-modelled. In this paper, we propose a new under-modelled BSI based method for TDE in reverberant environments. An under-modelled BSI algorithm is derived, which is based on maximizing the cross-correlation of the cross-filtered signals rather than minimizing the cross-relation error, and also exploits the sparsity of the early part of the RIR. For TDE, this new criterion can be viewed as a generalization of conventional cross-correlation-based TDE methods by considering a more realistic model for the early RIR. Depending on the microphone spacing, only a short early part of each RIR is identified, and the time delays are estimated based on the peak locations in the identified early RIRs. Experiments in different reverberant environments with speech source signals demonstrate the effectiveness of the proposed method

Development of a Sonic Sensor for Aircraft Applications

The field of aeroacoustics has been an area of constant research over the past six decades. Acoustic waves have some special characteristics that allow for heating, cooling, and even active flow control over airfoil shapes using synthetic jets and other methods. They can also be used to measure properties of the flow over an aircraft, including the free-stream pressure ratio, density ratio, and total temperature. The current measurement techniques to obtain these parameters applied to aircraft require a specific probe. It is desired to apply knowledge of acoustics to develop an aircraft sensor that can measure multiple flow properties with minimal impact to the flow field. Adding a sensor that can read total temperature, static temperature, airspeed, and angle of attack will have the added benefit of reducing the number of sensors sticking into the flow and may result in a reduction in failure mode analysis due to the minimization of the number of sensors on the aircraft. This work explores the applicability of sonic anemometry to aircraft for high subsonic and sonic speeds. A computational simulation is developed as a validation of the concept and low speed experiments are shown to validate the theory. This effort identifies the underlying issues associated with applying sonic anemometry to high-speed flows and provides methods to overcome them. This work investigates the use of phased array technology to increase the accuracy and applicability at the higher speeds and smaller footprints (lighter and fewer systems). Phased arrays use the constructive and destructive interference to boost and direct the desired signal, in this case, acoustic waves. These acoustic waves have been shown to provide haptic feedback and levitate small particles utilizing a relatively inexpensive ultrasonic phased array system. It is shown that the ultrasonic phased array overcomes the hydrodynamic noise to produce a strong signal for use in the calculation of the flow parameters up to the maximum speed tested. It is also shown that the signal is strong enough to produce consistent time delay estimations, via cross-correlation, with a 0.05 second sample time to integrate into modern air data systems.Ph.D

Advances in Architectural Acoustics

Satisfactory acoustics is crucial for the ability of spaces such as auditoriums and lecture rooms to perform their primary function. The acoustics of dwellings and offices greatly affects the quality of our life, since we are all consciously or subconsciously aware of the sounds to which we are daily subjected. Architectural acoustics, which encompasses room and building acoustics, is the scientific field that deals with these topics and can be defined as the study of generation, propagation, and effects of sound in enclosures. Modeling techniques, as well as related acoustic theories for accurately calculating the sound field, have been the center of many major new developments. In addition, the image conveyed by a purely physical description of sound would be incomplete without regarding human perception; hence, the interrelation between objective stimuli and subjective sensations is a field of important investigations. A holistic approach in terms of research and practice is the optimum way for solving the perplexing problems which arise in the design or refurbishment of spaces, since current trends in contemporary architecture, such as transparency, openness, and preference for bare sound-reflecting surfaces are continuing pushing the very limits of functional acoustics. All the advances in architectural acoustics gathered in this Special Issue, we hope that inspire researchers and acousticians to explore new directions in this age of scientific convergence

Engine Validation of Noise and Emission Reduction Technology Phase I

This final report has been prepared by Honeywell Aerospace, Phoenix, Arizona, a unit of Honeywell International, Inc., documenting work performed during the period December 2004 through August 2007 for the NASA Glenn Research Center, Cleveland, Ohio, under the Revolutionary Aero-Space Engine Research (RASER) Program, Contract No. NAS3-01136, Task Order 8, Engine Validation of Noise and Emission Reduction Technology Phase I. The NASA Task Manager was Dr. Joe Grady of the NASA Glenn Research Center. The NASA Contract Officer was Mr. Albert Spence of the NASA Glenn Research Center. This report is for a test program in which NASA funded engine validations of integrated technologies that reduce aircraft engine noise. These technologies address the reduction of engine fan and jet noise, and noise associated with propulsion/airframe integration. The results of these tests will be used by NASA to identify the engineering tradeoffs associated with the technologies that are needed to enable advanced engine systems to meet stringent goals for the reduction of noise. The objectives of this program are to (1) conduct system engineering and integration efforts to define the engine test-bed configuration; (2) develop selected noise reduction technologies to a technical maturity sufficient to enable engine testing and validation of those technologies in the FY06-07 time frame; (3) conduct engine tests designed to gain insight into the sources, mechanisms and characteristics of noise in the engines; and (4) establish baseline engine noise measurements for subsequent use in the evaluation of noise reduction