Spatial, Spectral, and Perceptual Nonlinear Noise Reduction for Hands-free Microphones in a Car

Speech enhancement in an automobile is a challenging problem because interference can come from engine noise, fans, music, wind, road noise, reverberation, echo, and passengers engaging in other conversations. Hands-free microphones make the situation worse because the strength of the desired speech signal reduces with increased distance between the microphone and talker. Automobile safety is improved when the driver can use a hands-free interface to phones and other devices instead of taking his eyes off the road. The demand for high quality hands-free communication in the automobile requires the introduction of more powerful algorithms. This thesis shows that a unique combination of five algorithms can achieve superior speech enhancement for a hands-free system when compared to beamforming or spectral subtraction alone. Several different designs were analyzed and tested before converging on the configuration that achieved the best results. Beamforming, voice activity detection, spectral subtraction, perceptual nonlinear weighting, and talker isolation via pitch tracking all work together in a complementary iterative manner to create a speech enhancement system capable of significantly enhancing real world speech signals. The following conclusions are supported by the simulation results using data recorded in a car and are in strong agreement with theory. Adaptive beamforming, like the Generalized Side-lobe Canceller (GSC), can be effectively used if the filters only adapt during silent data frames because too much of the desired speech is cancelled otherwise. Spectral subtraction removes stationary noise while perceptual weighting prevents the introduction of offensive audible noise artifacts. Talker isolation via pitch tracking can perform better when used after beamforming and spectral subtraction because of the higher accuracy obtained after initial noise removal. Iterating the algorithm once increases the accuracy of the Voice Activity Detection (VAD), which improves the overall performance of the algorithm. Placing the microphone(s) on the ceiling above the head and slightly forward of the desired talker appears to be the best location in an automobile based on the experiments performed in this thesis. Objective speech quality measures show that the algorithm removes a majority of the stationary noise in a hands-free environment of an automobile with relatively minimal speech distortion

A miniature, lowpower , intelligent sensor node for persistent acoustic surveillance

ABSTRACT The desire for persistent, long term surveillance and covertness places severe constraints on the power consumption of a sensor node. To achieve the desired endurance while minimizing the size of the node, it is imperative to use application-specific integrated circuits (ASICs) that deliver the required performance with maximal power efficiency while minimizing the amount of communication bandwidth needed. This paper reviews our ongoing effort to integrate several micropower devices for low-power wake-up detection, blind source separation and localization and pattern classification, and demonstrate the utility of the system in relevant surveillance applications. The capabilities of each module are presented in detail along with performance statistics measured during recent experiments

Aeroacoustics of sawtooth trailing-edge serrations under aerodynamic loading

The impact of aerodynamic loading on a serrated trailing edge is studied experimentally. Aerodynamic and acoustic measurements are conducted on a sawtooth-shaped trailing edge, retrofitted to a flat plate featuring a trailing-edge flap, and placed at incidence to the free-stream flow. The turbulent flow across the trailing edge is inspected by time-resolved three-dimensional velocity field measurements obtained from 4D-PIV, while the wall-pressure fluctuations are measured with surface-embedded microphones. Results discuss the relation between the velocity fluctuations over the serrations, the surface pressure fluctuations, and the far-field noise spectra. The aerodynamic analysis discusses the effect of counter-rotating vortex pairs, generated by the pressure imbalance across the edges of the serrations under loading. It is shown that the interaction of these vortices with the incoming turbulence affects the intensity of the wall-pressure spectrum at the outer rim of the serration surface. On the suction side, the intensity of the pressure fluctuations from the incoming boundary layer dominates over that induced by the vortex pairs. On the pressure side, instead, the velocity gradient prescribed by the vortex pairs produces a significant increase of the pressure fluctuations around the edges. The resulting spatial distribution of the wall-pressure fluctuations directly affects the far-field noise. Scattering predictions carried out with the wall-pressure fluctuations in the centre and root (on the suction side) exhibit good agreement with the measured noise in the low-frequency range, whereas using the surface pressure data at the tip of the serration (on the pressure side) yields a better prediction in the high-frequency range

ROBOTIC SOUND SOURCE LOCALIZATION AND TRACKING USING BIO-INSPIRED MINIATURE ACOUSTIC SENSORS

Sound source localization and tracking using auditory systems has been widely investigated for robotics applications due to their inherent advantages over other systems, such as vision based systems. Most existing robotic sound localization and tracking systems utilize conventional microphone arrays with different arrangements, which are inherently limited by a size constraint and are thus difficult to implement on miniature robots. To overcome the size constraint, sensors that mimic the mechanically coupled ear of fly Ormia have been previously developed. However, there has not been any attempt to study robotic sound source localization and tracking with these sensors. In this dissertation, robotic sound source localization and tracking using the miniature fly-ear-inspired sensors are studied for the first time. First, through investigation into the Cramer Rao lower bound (CRLB) and variance of the sound incident angle estimation, an enhanced understanding of the influence of the mechanical coupling on the performance of the fly-ear inspired sensor for sound localization is achieved. It is found that due to the mechanical coupling between the membranes, at its working frequency, the fly-ear inspired sensor can achieve an estimation of incident angle that is 100 time better than that of the conventional microphone pair with same signal-to-noise ratio in detection of the membrane deflection. Second, development of sound localization algorithms that can be used for robotic sound source localization and tracking using the fly-ear inspired sensors is carried out. Two methods are developed to estimate the sound incident angle based on the sensor output. One is based on model-free gradient descent method and the other is based on fuzzy logic. In the first approach, different localization schemes and different objective functions are investigated through numerical simulations, in which two-dimensional sound source localization is achieved without ambiguity. To address the slow convergence due to the iterative nature of the first approach, a novel fuzzy logic model of the fly-ear sensor is developed in the second approach for sound incident angle estimation. This model is studied in both simulations and experiments for localization of a stationary source and tracking a moving source in one dimension with a good performance. Third, nonlinear and quadratic-linear controllers are developed for control of the kinematics of a robot for sound source localization and tracking, which is implemented later in a mobile platform equipped with a microphone pair. Both homing onto a stationary source and tracking of a moving source with pre-defined paths are successfully demonstrated. Through this dissertation work, new knowledge on robotic sound source localization and tracking using fly-ear inspired sensors is created, which can serve as a basis for future study of sound source localization and tracking with miniature robots

High fidelity, multi-disciplinary analysis of flow in realistic weapon bays

To improve the stealthiness, and the efficiency of military aircraft, engineers moved carried weapons from external hand points, to weapons bays. However, the flow inside bays is turbulent, and characterised by strong broadband, and tonal noise. The open bay flow leads to variability in the released store trajectory, excites the missile, and bay structures, and reduces the aircraft stealthiness. This thesis aims to improve our understanding of real weapon bay flow, and suggests a method for quantifying the store trajectory variability. The main spatio-temporal characteristics of cavity flows are described using post-processing methods, like, SPL, OASPL, and wavelet transform. Also, the code HMB3 is validated for simulation of cavity flows, comparing Scale Adaptive (SAS) results with experiments. To further improve the understanding of the physics driving this flow, a simple model is presented, and compared to experiments. The results are promising, and the model is able to reproduce the cavity flow fluctuations both in space and time. To support measurements of the noise field around a cavity flow, beamforming is applied to the CFD results. This method was able of capturing the main sources of noise around the cavity, using a microphone array, and the mean flow to simulate the propagation of acoustic waves. Also, recommendations for future use of this technique are given. Developments were carried out for this thesis, and for the first time, a CFD code is reported to simulate the complete weapon bay operation, including door operation, store release, and store aeroelasticity. The different parts of the code are strongly coupled, and work together. Thanks to new capabilities of HMB3, this thesis shows more insight on the physics behind realistic weapon bay operation. The flow establishment during door opening is described, and appears to be important for store design, only if the doors are moving very fast. Store releases are simulated, and statistical analysis of the data is performed. A statistical metric was proposed to identify the minimum number of simulations necessary for capturing the mean and standard deviation of the trajectories. Using averaged, and filtered flow data, the trajectory phases were identified and the role of the pressure field inside the cavity was clarified. In addition, the aeroelasticity of the store was computed during carriage, door opening, and release phases, showing small deformations that may lead to structural fatigue. Thanks to the efficiency of the SAS method, a large number of simulations were performed, and more than 1800 cavity travel times were simulated. Simulation of the flow around a store in a supersonic flow, and at high attitude is described in an appendix of the thesis. Like a cavity, this flow has complex features that require advanced turbulence modelling to be simulated. In addition, novel cavity flow controls are investigated, and described in a restricted appendix of the thesis

Low noise amplifier design and noise cancellation for wireless hearing aids

Master'sMASTER OF ENGINEERIN