Single- and multi-microphone speech dereverberation using spectral enhancement

In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility

Digital Signal Processing Education: Technology and Tradition

In this paper we discuss a DSP course presented to both University students and to participants on industrial short courses. The "traditional" DSP course will typically run over one to two semesters and usually cover the fundamental mathematics of z-, Laplace and Fourier transforms, followed by the algorithm and application detail. In the course we will discuss, the use of advanced DSP software and integrated support software allow the presentation time to be greatly shortened and more focussed algorithm and application learning to be introduced. By combining the traditional lecture with the use of advanced DSP software, all harnessed by the web, we report on the objectives, syllabus, and mode of teaching

Development and application of spread-spectrum ultrasonic evaluation technique

A new approach to ultrasonic NDE called spread-spectrum ultrasonic evaluation (SSUE) is investigated. It regards the ultrasonic nondestructive evaluation as an acoustic-impulse-response estimation and characterization problem. This problem has been compared with the analogous problems of radio-detection-and-ranging from communications field and the seismic exploration problem of geophysics. Out of the various options for the impulse response estimation, the continuous pseudorandom signal correlation method has been shown to be the optimum for peak-power limited systems such as the ultrasonic NDE systems. The problem of self-noise and its consequences in pseudorandom correlation systems is investigated, followed by the development of various optimum and sub-optimum approaches to self-noise elimination. After verifying the theoretical results through computer simulations, a lab-grade SSUE instrument was developed and analyzed. Also, a new, efficient method for the implementation of DSP-based correlator is developed. The application of SSUE technique to various practical NDE situations like, flaw detection, velocity/thickness measurements, attenuation measurement, global integrity assessment, etc., was investigated through various laboratory experiments. It is concluded that the SSUE technique holds great promise for all ultrasonic NDE applications where high signal attenuation results into the loss of signal-to-noise ratios beyond workable limits;SSUE employs a non-traditional approach to ultrasonic NDE that makes it more robust and powerful. One significant feature of the SSUE technique is that it overcomes the maximum average power limitation of the existing techniques. Conventional pulsed ultrasonic NDE systems are peak power limited by the transducer breakdown voltage and the average power is limited by the narrow pulse duration which is important to maintain good resolution. In certain NDE applications there are factors other than the transducer peak power limitation, which limit the amplitude of the transmitted signal. In case of medical ultrasound devices, for example, the peak power limit arises from the risk of causing tissue damage. For such kind of applications, SSUE has a direct solution to increasing the average power while maintaining the resolution. Ultrasonic NDE instrument in a field or industrial environment is subject to all kinds of acoustic and electromagnetic interferences. This results into a degradation of instrument sensitivity and reliability. SSUE technique, by virtue of its robust operating principal, is capable of interference rejection to a much larger extent

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book

Neural architecture for echo suppression during sound source localization based on spiking neural cell models

Zusammenfassung Diese Arbeit untersucht die biologischen Ursachen des psycho-akustischen Präzedenz Effektes, der Menschen in die Lage versetzt, akustische Echos während der Lokalisation von Schallquellen zu unterdrücken. Sie enthält ein Modell zur Echo-Unterdrückung während der Schallquellenlokalisation, welches in technischen Systemen zur Mensch-Maschine Interaktion eingesetzt werden kann. Die Grundlagen dieses Modells wurden aus eigenen elektrophysiologischen Experimenten an der Mongolischen Wüstenrennmaus gewonnen. Die dabei erstmalig an der Wüstenrennmaus erzielten Ergebnisse, zeigen ein besonderes Verhalten spezifischer Zellen im Dorsalen Kern des Lateral Lemniscus, einer dedizierten Region des auditorischen Hirnstammes. Die dort sichtbare Langzeithemmung scheint die Grundlage für die Echounterdrückung in höheren auditorischen Zentren zu sein. Das entwickelte Model war in der Lage dieses Verhalten nachzubilden, und legt die Vermutung nahe, dass eine starke und zeitlich präzise Hyperpolarisation der zugrundeliegende physiologische Mechanismus dieses Verhaltens ist. Die entwickelte Neuronale Modellarchitektur modelliert das Innenohr und fünf wesentliche Kerne des auditorischen Hirnstammes in ihrer Verbindungsstruktur und internen Dynamik. Sie stellt einen neuen Typus neuronaler Modellierung dar, der als Spike-Interaktionsmodell (SIM) bezeichnet wird. SIM nutzen die präzise räumlich-zeitliche Interaktion einzelner Aktionspotentiale (Spikes) für die Kodierung und Verarbeitung neuronaler Informationen. Die Basis dafür bilden Integrate-and-Fire Neuronenmodelle sowie Hebb'sche Synapsen, welche um speziell entwickelte dynamische Kernfunktionen erweitert wurden. Das Modell ist in der Lage, Zeitdifferenzen von 10 mykrosekunden zu detektieren und basiert auf den Prinzipien der zeitlichen und räumlichen Koinzidenz sowie der präzisen lokalen Inhibition. Es besteht ausschließlich aus Elementen einer eigens entwickelten Neuronalen Basisbibliothek (NBL) die speziell für die Modellierung verschiedenster Spike- Interaktionsmodelle entworfen wurde. Diese Bibliothek erweitert die kommerziell verfügbare dynamische Simulationsumgebung von MATLAB/SIMULINK um verschiedene Modelle von Neuronen und Synapsen, welche die intrinsischen dynamischen Eigenschaften von Nervenzellen nachbilden. Die Nutzung dieser Bibliothek versetzt sowohl den Ingenieur als auch den Biologen in die Lage, eigene, biologisch plausible, Modelle der neuronalen Informationsverarbeitung ohne detaillierte Programmierkenntnisse zu entwickeln. Die grafische Oberfläche ermöglicht strukturelle sowie parametrische Modifikationen und ist in der Lage, den Zeitverlauf mikroskopischer Zellpotentiale aber auch makroskopischer Spikemuster während und nach der Simulation darzustellen. Zwei grundlegende Elemente der Neuronalen Basisbibliothek wurden zur Implementierung als spezielle analog-digitale Schaltungen vorbereitet. Erste Silizium Implementierungen durch das Team des DFG Graduiertenkollegs GRK 164 konnten die Möglichkeit einer vollparallelen on line Verarbeitung von Schallsignalen nachweisen. Durch Zuhilfenahme des im GRK entwickelten automatisierten Layout Generators wird es möglich, spezielle Prozessoren zur Anwendung biologischer Verarbeitungsprinzipien in technischen Systemen zu entwickeln. Diese Prozessoren unterscheiden sich grundlegend von den klassischen von Neumann Prozessoren indem sie räumlich und zeitlich verteilte Spikemuster, anstatt sequentieller binärer Werte zur Informationsrepräsentation nutzen. Sie erweitern das digitale Kodierungsprinzip durch die Dimensionen des Raumes (2 dimensionale Nachbarschaft) der Zeit (Frequenz, Phase und Amplitude) sowie der zeitlichen Dynamik analoger Potentialverläufe. Diese Dissertation besteht aus sieben Kapiteln, welche den verschiedenen Bereichen der Computational Neuroscience gewidmet sind. Kapitel 1 beschreibt die Motivation dieser Arbeit welche aus der Absicht rühren, biologische Prinzipien der Schallverarbeitung zu erforschen und für technische Systeme während der Interaktion mit dem Menschen nutzbar zu machen. Zusätzlich werden fünf Gründe für die Nutzung von Spike-Interaktionsmodellen angeführt sowie deren neuartiger Charakter beschrieben. Kapitel 2 führt die biologischen Prinzipien der Schallquellenlokalisation und den psychoakustischen Präzedenz Effekt ein. Aktuelle Hypothesen zur Entstehung dieses Effektes werden anhand ausgewählter experimenteller Ergebnisse verschiedener Forschungsgruppen diskutiert. Kapitel 3 beschreibt die entwickelte Neuronale Basisbibliothek und führt die einzelnen neuronalen Simulationselemente ein. Es erklärt die zugrundeliegenden mathematischen Funktionen der dynamischen Komponenten und beschreibt deren generelle Einsetzbarkeit zur dynamischen Simulation spikebasierter Neuronaler Netzwerke. Kapitel 4 enthält ein speziell entworfenes Modell des auditorischen Hirnstammes beginnend mit den Filterkaskaden zur Simulation des Innenohres, sich fortsetzend über mehr als 200 Zellen und 400 Synapsen in 5 auditorischen Kernen bis zum Richtungssensor im Bereich des auditorischen Mittelhirns. Es stellt die verwendeten Strukturen und Parameter vor und enthält grundlegende Hinweise zur Nutzung der Simulationsumgebung. Kapitel 5 besteht aus drei Abschnitten, wobei der erste Abschnitt die Experimentalbedingungen und Ergebnisse der eigens durchgeführten Tierversuche beschreibt. Der zweite Abschnitt stellt die Ergebnisse von 104 Modellversuchen zur Simulationen psycho-akustischer Effekte dar, welche u.a. die Fähigkeit des Modells zur Nachbildung des Präzedenz Effektes testen. Schließlich beschreibt der letzte Abschnitt die Ergebnisse der 54 unter realen Umweltbedingungen durchgeführten Experimente. Dabei kamen Signale zur Anwendung, welche in normalen sowie besonders stark verhallten Räumen aufgezeichnet wurden. Kapitel 6 vergleicht diese Ergebnisse mit anderen biologisch motivierten und technischen Verfahren zur Echounterdrückung und Schallquellenlokalisation und führt den aktuellen Status der Hardwareimplementierung ein. Kapitel 7 enthält schließlich eine kurze Zusammenfassung und einen Ausblick auf weitere Forschungsobjekte und geplante Aktivitäten. Diese Arbeit möchte zur Entwicklung der Computational Neuroscience beitragen, indem sie versucht, in einem speziellen Anwendungsfeld die Lücke zwischen biologischen Erkenntnissen, rechentechnischen Modellen und Hardware Engineering zu schließen. Sie empfiehlt ein neues räumlich-zeitliches Paradigma der dynamischen Informationsverarbeitung zur Erschließung biologischer Prinzipien der Informationsverarbeitung für technische Anwendungen.This thesis investigates the biological background of the psycho-acoustical precedence effect, enabling humans to suppress echoes during the localization of sound sources. It provides a technically feasible and biologically plausible model for sound source localization under echoic conditions, ready to be used by technical systems during man-machine interactions. The model is based upon own electro-physiological experiments in the mongolian gerbil. The first time in gerbils obtained results reveal a special behavior of specific cells of the dorsal nucleus of the lateral lemniscus (DNLL) - a distinct region in the auditory brainstem. The explored persistent inhibition effect of these cells seems to account for the base of echo suppression at higher auditory centers. The developed model proved capable to duplicate this behavior and suggests, that a strong and timely precise hyperpolarization is the basic mechanism behind this cell behavior. The developed neural architecture models the inner ear as well as five major nuclei of the auditory brainstem in their connectivity and intrinsic dynamics. It represents a new type of neural modeling described as Spike Interaction Models (SIM). SIM use the precise spatio-temporal interaction of single spike events for coding and processing of neural information. Their basic elements are Integrate-and-Fire Neurons and Hebbian synapses, which have been extended by specially designed dynamic transfer functions. The model is capable to detect time differences as small as 10 mircrosecondes and employs the principles of coincidence detection and precise local inhibition for auditory processing. It consists exclusively of elements of a specifically designed Neural Base Library (NBL), which has been developed for multi purpose modeling of Spike Interaction Models. This library extends the commercially available dynamic simulation environment of MATLAB/SIMULINK by different models of neurons and synapses simulating the intrinsic dynamic properties of neural cells. The usage of this library enables engineers as well as biologists to design their own, biologically plausible models of neural information processing without the need for detailed programming skills. Its graphical interface provides access to structural as well as parametric changes and is capable to display the time course of microscopic cell parameters as well as macroscopic firing pattern during simulations and thereafter. Two basic elements of the Neural Base Library have been prepared for implementation by specialized mixed analog-digital circuitry. First silicon implementations were realized by the team of the DFG Graduiertenkolleg GRK 164 and proved the possibility of fully parallel on line processing of sounds. By using the automated layout processor under development in the Graduiertenkolleg, it will be possible to design specific processors in order to apply theprinciples of distributed biological information processing to technical systems. These processors differ from classical von Neumann processors by the use of spatio temporal spike pattern instead of sequential binary values. They will extend the digital coding principle by the dimensions of space (spatial neighborhood), time (frequency, phase and amplitude) as well as the dynamics of analog potentials and introduce a new type of information processing. This thesis consists of seven chapters, dedicated to the different areas of computational neuroscience. Chapter 1: provides the motivation of this study arising from the attempt to investigate the biological principles of sound processing and make them available to technical systems interacting with humans under real world conditions. Furthermore, five reasons to use spike interaction models are given and their novel characteristics are discussed. Chapter 2: introduces the biological principles of sound source localization and the precedence effect. Current hypothesis on echo suppression and the underlying principles of the precedence effect are discussed by reference to a small selection of physiological and psycho-acoustical experiments. Chapter 3: describes the developed neural base library and introduces each of the designed neural simulation elements. It also explains the developed mathematical functions of the dynamic compartments and describes their general usage for dynamic simulation of spiking neural networks. Chapter 4: introduces the developed specific model of the auditory brainstem, starting from the filtering cascade in the inner ear via more than 200 cells and 400 synapses in five auditory regions up to the directional sensor at the level of the auditory midbrain. It displays the employed parameter sets and contains basic hints for the set up and configuration of the simulation environment. Chapter 5: consists of three sections, whereas the first one describes the set up and results of the own electro-physiological experiments. The second describes the results of 104 model simulations, performed to test the models ability to duplicate psycho-acoustical effects like the precedence effect. Finally, the last section of this chapter contains the results of 54 real world experiments using natural sound signals, recorded under normal as well as highly reverberating conditions. Chapter 6: compares the achieved results to other biologically motivated and technical models for echo suppression and sound source localization and introduces the current status of silicon implementation. Chapter 7: finally provides a short summary and an outlook toward future research subjects and areas of investigation. This thesis aims to contribute to the field of computational neuroscience by bridging the gap between biological investigation, computational modeling and silicon engineering in a specific field of application. It suggests a new spatio-temporal paradigm of information processing in order to access the capabilities of biological systems for technical applications

Design, analysis and evaluation of sigma-delta based beamformers for medical ultrasound imaging applications

The inherent analogue nature of medical ultrasound signals in conjunction with the abundant merits provided by digital image acquisition, together with the increasing use of relatively simple front-end circuitries, have created considerable demand for single-bit beamformers in digital ultrasound imaging systems. Furthermore, the increasing need to design lightweight ultrasound systems with low power consumption and low noise, provide ample justification for development and innovation in the use of single-bit beamformers in ultrasound imaging systems. The overall aim of this research program is to investigate, establish, develop and confirm through a combination of theoretical analysis and detailed simulations, that utilize raw phantom data sets, suitable techniques for the design of simple-to-implement hardware efficient digital ultrasound beamformers to address the requirements for 3D scanners with large channel counts, as well as portable and lightweight ultrasound scanners for point-of-care applications and intravascular imaging systems. In addition, the stability boundaries of higher-order High-Pass (HP) and Band-Pass (BP) Σ−Δ modulators for single- and dual- sinusoidal inputs are determined using quasi-linear modeling together with the describing-function method, to more accurately model the modulator quantizer. The theoretical results are shown to be in good agreement with the simulation results for a variety of input amplitudes, bandwidths, and modulator orders. The proposed mathematical models of the quantizer will immensely help speed up the design of higher order HP and BP Σ−Δ modulators to be applicable for digital ultrasound beamformers. Finally, a user friendly design and performance evaluation tool for LP, BP and HP modulators is developed. This toolbox, which uses various design methodologies and covers an assortment of modulators topologies, is intended to accelerate the design process and evaluation of modulators. This design tool is further developed to enable the design, analysis and evaluation of beamformer structures including the noise analyses of the final B-scan images. Thus, this tool will allow researchers and practitioners to design and verify different reconstruction filters and analyze the results directly on the B-scan ultrasound images thereby saving considerable time and effort