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

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Speech Detection Using Gammatone Features And One-class Support Vector Machine

A network gateway is a mechanism which provides protocol translation and/or validation of network traffic using the metadata contained in network packets. For media applications such as Voice-over-IP, the portion of the packets containing speech data cannot be verified and can provide a means of maliciously transporting code or sensitive data undetected. One solution to this problem is through Voice Activity Detection (VAD). Many VAD’s rely on time-domain features and simple thresholds for efficient speech detection however this doesn’t say much about the signal being passed. More sophisticated methods employ machine learning algorithms, but train on specific noises intended for a target environment. Validating speech under a variety of unknown conditions must be possible; as well as differentiating between speech and nonspeech data embedded within the packets. A real-time speech detection method is proposed that relies only on a clean speech model for detection. Through the use of Gammatone filter bank processing, the Cepstrum and several frequency domain features are used to train a One-Class Support Vector Machine which provides a clean-speech model irrespective of environmental noise. A Wiener filter is used to provide improved operation for harsh noise environments. Greater than 90% detection accuracy is achieved for clean speech with approximately 70% accuracy for SNR as low as 5d

Underwater acoustic communications

The underwater acoustic medium poses unique challenges to the design of robust, high throughput digital communications. The aim of this work is to identify modulation and receiver processing techniques to enable the reliable transfer of data at high rate, at range between two, potentially mobile parties using acoustics. More generally, this work seeks to investigate techniques to effectively communicate between two or more parties over a wide range of channel conditions where data rate is a key but not always the absolute performance requirement. Understanding the intrinsic ocean mechanisms that influence signal coherence, the relationship between signal coherence and optimum signal design, and the development of robust modulation and receiver processing techniques are the main areas of study within this work. New and established signal design, modulation, synchronisation, equalisation and spatial processing techniques are investigated. Several new, innovative techniques are presented which seek to improve the robustness of ‘classical’ solutions to the underwater acoustic communications problem. The performance of these techniques to mitigate the severe temporal dispersion of the underwater channel and its unique temporal variability are assessed. A candidate modulation, synchronisation and equalisation architecture is proposed based on a spatial-temporal adaptive signal processing (STAP) receiver. Comprehensive simulation results are presented to demonstrate the performance of the candidate receiver to time selective, frequency selective and spatially selective channel behaviour. Several innovative techniques are presented which maximise system performance over a wider range of operational and environmental conditions. Field trials results are presented based on system evaluation over a wide range of geographically distinct environments demonstrating system performance over a diverse range of ocean bathymetry, topography and background noise conditions. A real time implementation of the system is reported and field trials results presented demonstrating the capability of the system to support a wide range of data formats including video at useful frame rates. Within this work, several novel techniques have been developed which have extended the state of the art in high data rate underwater communications:- • Robust, high fidelity open loop synchronisation techniques capable of operating at marginal signal-to-noise ratios over a wide range of severely time spread environments. These high probability of synchronisation, low probability of false alarm techniques, provide the means for ‘burst’ open loop synchronisation in time, Doppler and space (bearing). The techniques have been demonstrated in communication and position fixing/navigation systems to provide repeatable range accuracy’s to centimetric order. • Novel closed loop synchronisation compensation for STAP receiver architectures. Specifically, this work has demonstrated the performance benefits of including both delay lock loop (DLL) and phase lock loop (PLL) support for acoustic adaptive receivers to offload tracking effort from the fractional feedforward equaliser section. It has been shown that the addition of a DLL/PLL outperforms the PLL only case for Doppler errors exceeding a few fractions of a knot. • Recycling of training data has been demonstrated as a potentially useful means to improve equaliser convergence in difficult acoustic channels. With suitable processing power, training data recycling introduces no additional transmission time overhead, which may be a limiting factor in battery powered applications. • Forward and time reverse decoding of packet data has been demonstrated as an effective means to overcome some non-minimum phase channel conditions. It has also been shown that there may be further benefits in terms of improved bit error performance, by exploiting concurrent forward and backward symbol data under modest channel conditions. • Several wideband techniques have been developed and demonstrated to be effective at resolving and coherently tracking difficult doubly spread acoustic channels. In particular, wideband spread spectrum techniques have been shown to be effective at resolving acoustic multipath, and with the aid of independent delay lock loops, track individual path arrivals. Techniques have been developed which can effect coherent or non-coherent recombination of these paths with a view to improving the robustness of an acoustic link operating at very low signal-to-noise levels. • Demonstrated throughputs of up to 41kbps in a difficult, tropical environment, featuring significant biological noise levels for mobile platforms at range up to 1.5km. • Demonstrated throughputs of between 300bps and 1600bps in a shallow, reverberant environment, at a range up to 21km at LF. • Implemented and demonstrated all algorithms in real time systems

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

International audienc