System approach to robust acoustic echo cancellation through semi-blind source separation based on independent component analysis

We live in a dynamic world full of noises and interferences. The conventional acoustic echo cancellation (AEC) framework based on the least mean square (LMS) algorithm by itself lacks the ability to handle many secondary signals that interfere with the adaptive filtering process, e.g., local speech and background noise. In this dissertation, we build a foundation for what we refer to as the system approach to signal enhancement as we focus on the AEC problem. We first propose the residual echo enhancement (REE) technique that utilizes the error recovery nonlinearity (ERN) to "enhances" the filter estimation error prior to the filter adaptation. The single-channel AEC problem can be viewed as a special case of semi-blind source separation (SBSS) where one of the source signals is partially known, i.e., the far-end microphone signal that generates the near-end acoustic echo. SBSS optimized via independent component analysis (ICA) leads to the system combination of the LMS algorithm with the ERN that allows for continuous and stable adaptation even during double talk. Second, we extend the system perspective to the decorrelation problem for AEC, where we show that the REE procedure can be applied effectively in a multi-channel AEC (MCAEC) setting to indirectly assist the recovery of lost AEC performance due to inter-channel correlation, known generally as the "non-uniqueness" problem. We develop a novel, computationally efficient technique of frequency-domain resampling (FDR) that effectively alleviates the non-uniqueness problem directly while introducing minimal distortion to signal quality and statistics. We also apply the system approach to the multi-delay filter (MDF) that suffers from the inter-block correlation problem. Finally, we generalize the MCAEC problem in the SBSS framework and discuss many issues related to the implementation of an SBSS system. We propose a constrained batch-online implementation of SBSS that stabilizes the convergence behavior even in the worst case scenario of a single far-end talker along with the non-uniqueness condition on the far-end mixing system. The proposed techniques are developed from a pragmatic standpoint, motivated by real-world problems in acoustic and audio signal processing. Generalization of the orthogonality principle to the system level of an AEC problem allows us to relate AEC to source separation that seeks to maximize the independence, hence implicitly the orthogonality, not only between the error signal and the far-end signal, but rather, among all signals involved. The system approach, for which the REE paradigm is just one realization, enables the encompassing of many traditional signal enhancement techniques in analytically consistent yet practically effective manner for solving the enhancement problem in a very noisy and disruptive acoustic mixing environment.PhDCommittee Chair: Biing-Hwang Juang; Committee Member: Brani Vidakovic; Committee Member: David V. Anderson; Committee Member: Jeff S. Shamma; Committee Member: Xiaoli M

Doctor of Philosophy

dissertationHearing aids suffer from the problem of acoustic feedback that limits the gain provided by hearing aids. Moreover, the output sound quality of hearing aids may be compromised in the presence of background acoustic noise. Digital hearing aids use advanced signal processing to reduce acoustic feedback and background noise to improve the output sound quality. However, it is known that the output sound quality of digital hearing aids deteriorates as the hearing aid gain is increased. Furthermore, popular subband or transform domain digital signal processing in modern hearing aids introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. In this dissertation, we employ a variable, frequency-dependent gain function that is lower at frequencies of the incoming signal where the information is perceptually insignificant. In addition, the method of this dissertation automatically identifies and suppresses residual acoustical feedback components at frequencies that have the potential to drive the system to instability. The suppressed frequency components are monitored and the suppression is removed when such frequencies no longer pose a threat to drive the hearing aid system into instability. Together, the method of this dissertation provides more stable gain over traditional methods by reducing acoustical coupling between the microphone and the loudspeaker of a hearing aid. In addition, the method of this dissertation performs necessary hearing aid signal processing with low-delay characteristics. The central idea for the low-delay hearing aid signal processing is a spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. Finally, the method of this dissertation switches to a least-squares adaptation scheme with linear complexity at the onset of howling. The method adapts to the altered feedback path quickly and allows the patient to not lose perceivable information. The complexity of the least-squares estimate is reduced by reformulating the least-squares estimate into a Toeplitz system and solving it with a direct Toeplitz solver. The increase in stable gain over traditional methods and the output sound quality were evaluated with psychoacoustic experiments on normal-hearing listeners with speech and music signals. The results indicate that the method of this dissertation provides 8 to 12 dB more hearing aid gain than feedback cancelers with traditional fixed gain functions. Furthermore, experimental results obtained with real world hearing aid gain profiles indicate that the method of this dissertation provides less distortion in the output sound quality than classical feedback cancelers, enabling the use of more comfortable style hearing aids for patients with moderate to profound hearing loss. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this dissertation exhibits much smaller forward-path delays with superior howling suppression capability

Adaptive Algorithms for Intelligent Acoustic Interfaces

Modern speech communications are evolving towards a new direction which involves users in a more perceptive way. That is the immersive experience, which may be considered as the “last-mile” problem of telecommunications. One of the main feature of immersive communications is the distant-talking, i.e. the hands-free (in the broad sense) speech communications without bodyworn or tethered microphones that takes place in a multisource environment where interfering signals may degrade the communication quality and the intelligibility of the desired speech source. In order to preserve speech quality intelligent acoustic interfaces may be used. An intelligent acoustic interface may comprise multiple microphones and loudspeakers and its peculiarity is to model the acoustic channel in order to adapt to user requirements and to environment conditions. This is the reason why intelligent acoustic interfaces are based on adaptive filtering algorithms. The acoustic path modelling entails a set of problems which have to be taken into account in designing an adaptive filtering algorithm. Such problems may be basically generated by a linear or a nonlinear process and can be tackled respectively by linear or nonlinear adaptive algorithms. In this work we consider such modelling problems and we propose novel effective adaptive algorithms that allow acoustic interfaces to be robust against any interfering signals, thus preserving the perceived quality of desired speech signals. As regards linear adaptive algorithms, a class of adaptive filters based on the sparse nature of the acoustic impulse response has been recently proposed. We adopt such class of adaptive filters, named proportionate adaptive filters, and derive a general framework from which it is possible to derive any linear adaptive algorithm. Using such framework we also propose some efficient proportionate adaptive algorithms, expressly designed to tackle problems of a linear nature. On the other side, in order to address problems deriving from a nonlinear process, we propose a novel filtering model which performs a nonlinear transformations by means of functional links. Using such nonlinear model, we propose functional link adaptive filters which provide an efficient solution to the modelling of a nonlinear acoustic channel. Finally, we introduce robust filtering architectures based on adaptive combinations of filters that allow acoustic interfaces to more effectively adapt to environment conditions, thus providing a powerful mean to immersive speech communications

Adaptive Algorithms for Intelligent Acoustic Interfaces

Modern speech communications are evolving towards a new direction which involves users in a more perceptive way. That is the immersive experience, which may be considered as the “last-mile” problem of telecommunications. One of the main feature of immersive communications is the distant-talking, i.e. the hands-free (in the broad sense) speech communications without bodyworn or tethered microphones that takes place in a multisource environment where interfering signals may degrade the communication quality and the intelligibility of the desired speech source. In order to preserve speech quality intelligent acoustic interfaces may be used. An intelligent acoustic interface may comprise multiple microphones and loudspeakers and its peculiarity is to model the acoustic channel in order to adapt to user requirements and to environment conditions. This is the reason why intelligent acoustic interfaces are based on adaptive filtering algorithms. The acoustic path modelling entails a set of problems which have to be taken into account in designing an adaptive filtering algorithm. Such problems may be basically generated by a linear or a nonlinear process and can be tackled respectively by linear or nonlinear adaptive algorithms. In this work we consider such modelling problems and we propose novel effective adaptive algorithms that allow acoustic interfaces to be robust against any interfering signals, thus preserving the perceived quality of desired speech signals. As regards linear adaptive algorithms, a class of adaptive filters based on the sparse nature of the acoustic impulse response has been recently proposed. We adopt such class of adaptive filters, named proportionate adaptive filters, and derive a general framework from which it is possible to derive any linear adaptive algorithm. Using such framework we also propose some efficient proportionate adaptive algorithms, expressly designed to tackle problems of a linear nature. On the other side, in order to address problems deriving from a nonlinear process, we propose a novel filtering model which performs a nonlinear transformations by means of functional links. Using such nonlinear model, we propose functional link adaptive filters which provide an efficient solution to the modelling of a nonlinear acoustic channel. Finally, we introduce robust filtering architectures based on adaptive combinations of filters that allow acoustic interfaces to more effectively adapt to environment conditions, thus providing a powerful mean to immersive speech communications

Effective and Efficient Non-Destructive Testing of Large and Complex Shaped Aircraft Structures

The main aim of the research described within this thesis is to develop methodologies that enhance the defect detection capabilities of nondestructive testing (NDT) for the aircraft industry. Modem aircraft non-destructive testing requires the detection of small defects in large complex shaped components. Research has therefore focused on the limitations of ultrasonic, radioscopic and shearographic methods and the complimentary aspects associated with each method. The work has identified many parameters that have significant effect on successful defect detection and has developed methods for assessing NDT systems capabilities by noise analysis, excitation performance and error contributions attributed to the positioning of sensors. The work has resulted in 1. The demonstration that positional accuracy when ultrasonic testing has a significant effect on defect detection and a method to measure positional accuracy by evaluating the compensation required in a ten axis scanning system has revealed limitsio the achievable defect detection when using complex geometry scanning systems. 2. A method to reliably detect 15 micron voids in a diffusion bonded joint at ultrasonic frequencies of 20 MHz and above by optimising transducer excitation, focussing and normalisation. 3. A method of determining the minimum detectable ultrasonic attenuation variation by plotting the measuring error when calibrating the alignment of a ten axis scanning system. 4. A new formula for the calculation of the optimum magnification for digital radiography. The formula is applicable for focal spot sizes less than 0.1 mm. 5. A practical method of measuring the detection capabilities of a digital radiographic system by calculating the modulation transfer function and the noise power spectrum from a reference image. 6. The practical application of digital radiography to the inspection of super plastically formed ditThsion bonded titanium (SPFDB) and carbon fibre composite structure has been demonstrated but has also been supported by quantitative measurement of the imaging systems capabilities. 7. A method of integrating all the modules of the shearography system that provides significant improvement in the minimum defect detection capability for which a patent has been granted. 8. The matching of the applied stress to the data capture and processing during a shearographic inspection which again contributes significantly to the defect detection capability. 9. The testing and validation of the Parker and Salter [1999] temporal unwrapping and laser illumination work has led to the realisation that producing a pressure drop that would result in a linear change in surface deformation over time is difficult to achieve. 10. The defect detection capabilities achievable by thermal stressing during a shearographic inspection have been discovered by applying the pressure drop algorithms to a thermally stressed part. 11. The minimum surface displacement measurable by a shearography system and therefore the defect detection capabilities can be determined by analysing the signal to noise ratio of a transition from a black (poor reflecting surface) to white (good reflecting surface). The quantisation range for the signal to noise ratio is then used in the Hung [1982] formula to calculate the minimum displacement. Many of the research aspects contained within this thesis are cuffently being implemented within the production inspection process at BAE Samlesbury

Non Linear Ultrasound Doppler and the Detection of Targeted Contrast Agents

One of the main challenges in molecular imaging with targeted contrast agents is the detection and discrimination of attached agents from the rest of the signals originating from freely flowing agents and tissue. The aim of this thesis was to develop methods for the detection of targeted microbubbles. One approach consisted of investigating the use of nonlinear Doppler for this purpose. Nonlinear Doppler enables the differentiation of moving from non-moving and linear from nonlinear scattering. Targeted microbubbles are static and nonlinear scatterers and they should be detected using this technique. A novel nonlinear Doppler technique: Pulse subtraction Doppler, was developed and compared to pulse inversion Doppler. It is shown that both techniques lead to similar Doppler spectra and depending on the medical applications and the equipment limitations, both techniques have benefits. This served as a starting point for the derivation of a generalised nonlinear Doppler technique, based on combined linear pulse pair sequences and tested in a simulation study. The response from a single microbubble was simulated for different pulse combinations and the pulse sequences were compared with regards to criteria specific to imaging requirements. It was shown that depending on initially set criteria, such as transmitted energy, mechanical index or scanner characteristics, certain pulse combinations offer alternatives to the current imaging modalities and allow to take into account specific constrains due to the targeted application/equipment. Furthermore, the proposed approach is directly applicable in a strict non linear imaging approach, without Doppler processing. An in vitro phantom was designed in order to assess pulse subtraction Doppler for the detection and discrimination of static nonlinear microbubbles in the presence of free flowing ones. It was shown that pulse subtraction Doppler enables such discrimination and the practicability for in vivo situations is discussed. The pulse subtraction Doppler sequences were also tested on a phantom containing magnetic bubbles. It was shown that the magnetic bubbles can be immobilised through a magnetic field to a specific region of interest under flow conditions. The bubbles also showed to be acoustically detectable and to scatter linearly at diagnostic driving pressures. Preliminary work regarding experimental biotinylated microbubbles and their attachment to streptavidin coated surfaces is also presented. Due to their proximity to a wall, researchers have found that targeted microbubbles exhibit different acoustic signatures compared to free ones and this knowledge can improve their detection techniques. The behaviour of microbubbles against a membrane of varying stiffness was also studied through high speed camera observations. It was found both experimentally and by comparison to theoretical modelling that within the stiffness range of human blood vessels the change in acoustical behaviour of microbubbles is negligible. This thesis has taken two complementary research approaches which have shown to constitute advancements for the detection and discrimination of targeted microbubbles

Effective and efficient non-destructive testing of large and complex shaped aircraft structures

The main aim of the research described within this thesis is to develop methodologies that enhance the defect detection capabilities of nondestructive testing (NDT) for the aircraft industry. Modem aircraft non-destructive testing requires the detection of small defects in large complex shaped components. Research has therefore focused on the limitations of ultrasonic, radioscopic and shearographic methods and the complimentary aspects associated with each method. The work has identified many parameters that have significant effect on successful defect detection and has developed methods for assessing NDT systems capabilities by noise analysis, excitation performance and error contributions attributed to the positioning of sensors. The work has resulted in 1. The demonstration that positional accuracy when ultrasonic testing has a significant effect on defect detection and a method to measure positional accuracy by evaluating the compensation required in a ten axis scanning system has revealed limitsio the achievable defect detection when using complex geometry scanning systems. 2. A method to reliably detect 15 micron voids in a diffusion bonded joint at ultrasonic frequencies of 20 MHz and above by optimising transducer excitation, focussing and normalisation. 3. A method of determining the minimum detectable ultrasonic attenuation variation by plotting the measuring error when calibrating the alignment of a ten axis scanning system. 4. A new formula for the calculation of the optimum magnification for digital radiography. The formula is applicable for focal spot sizes less than 0.1 mm. 5. A practical method of measuring the detection capabilities of a digital radiographic system by calculating the modulation transfer function and the noise power spectrum from a reference image. 6. The practical application of digital radiography to the inspection of super plastically formed ditThsion bonded titanium (SPFDB) and carbon fibre composite structure has been demonstrated but has also been supported by quantitative measurement of the imaging systems capabilities. 7. A method of integrating all the modules of the shearography system that provides significant improvement in the minimum defect detection capability for which a patent has been granted. 8. The matching of the applied stress to the data capture and processing during a shearographic inspection which again contributes significantly to the defect detection capability. 9. The testing and validation of the Parker and Salter [1999] temporal unwrapping and laser illumination work has led to the realisation that producing a pressure drop that would result in a linear change in surface deformation over time is difficult to achieve. 10. The defect detection capabilities achievable by thermal stressing during a shearographic inspection have been discovered by applying the pressure drop algorithms to a thermally stressed part. 11. The minimum surface displacement measurable by a shearography system and therefore the defect detection capabilities can be determined by analysing the signal to noise ratio of a transition from a black (poor reflecting surface) to white (good reflecting surface). The quantisation range for the signal to noise ratio is then used in the Hung [1982] formula to calculate the minimum displacement. Many of the research aspects contained within this thesis are cuffently being implemented within the production inspection process at BAE Samlesbury.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Active adaptive cancellation of sound in ducts

Thesis (M. Eng. Sc.) -- University of Adelaide, Dept. of Electrical and Electronic Engineering, 1986