Distributed and Collaborative Processing of Audio Signals: Algorithms, Tools and Applications

Tesis por compendio[ES] Esta tesis se enmarca en el campo de las Tecnologías de la Información y las Comunicaciones (TIC), especialmente en el área del procesado digital de la señal. En la actualidad, y debido al auge del Internet de los cosas (IoT), existe un creciente interés por las redes de sensores inalámbricos (WSN), es decir, redes compuestas de diferentes tipos de dispositivos específicamente distribuidos en una determinada zona para realizar diferentes tareas de procesado de señal. Estos dispositivos o nodos suelen estar equipados con transductores electroacústicos así como con potentes y eficientes procesadores con capacidad de comunicación. En el caso particular de las redes de sensores acústicos (ASN), los nodos se dedican a resolver diferentes tareas de procesado de señales acústicas. El desarrollo de potentes sistemas de procesado centralizado han permitido aumentar el número de canales de audio, ampliar el área de control o implementar algoritmos más complejos. En la mayoría de los casos, una topología de ASN distribuida puede ser deseable debido a varios factores tales como el número limitado de canales utilizados por los dispositivos de adquisición y reproducción de audio, la conveniencia de un sistema escalable o las altas exigencias computacionales de los sistemas centralizados. Todos estos aspectos pueden llevar a la utilización de nuevas técnicas de procesado distribuido de señales con el fin de aplicarlas en ASNs. Para ello, una de las principales aportaciones de esta tesis es el desarrollo de algoritmos de filtrado adaptativo para sistemas de audio multicanal en redes distribuidas. Es importante tener en cuenta que, para aplicaciones de control del campo sonoro (SFC), como el control activo de ruido (ANC) o la ecualización activa de ruido (ANE), los nodos acústicos deben estar equipados con actuadores con el fin de controlar y modificar el campo sonoro. Sin embargo, la mayoría de las propuestas de redes distribuidas adaptativas utilizadas para resolver problemas de control del campo sonoro no tienen en cuenta que los nodos pueden interferir o modificar el comportamiento del resto. Por lo tanto, otra contribución destacable de esta tesis se centra en el análisis de cómo el sistema acústico afecta el comportamiento de los nodos dentro de una ASN. En los casos en que el entorno acústico afecta negativamente a la estabilidad del sistema, se han propuesto varias estrategias distribuidas para resolver el problema de interferencia acústica con el objetivo de estabilizar los sistemas de ANC. En el diseño de los algoritmos distribuidos también se han tenido en cuenta aspectos de implementación práctica. Además, con el objetivo de crear perfiles de ecualización diferentes en zonas de escucha independientes en presencia de ruidos multitonales, se han presentado varios algoritmos distribuidos de ANE en banda estrecha y banda ancha sobre una ASN con una comunicación colaborativa y compuesta por nodos acústicos. Se presentan además resultados experimentales para validar el uso de los algoritmos distribuidos propuestos en el trabajo para aplicaciones prácticas. Para ello, se ha diseñado un software de simulación acústica que permite analizar el rendimiento de los algoritmos desarrollados en la tesis. Finalmente, se ha realizado una implementación práctica que permite ejecutar aplicaciones multicanal de SFC. Para ello, se ha desarrollado un prototipo en tiempo real que controla las aplicaciones de ANC y ANE utilizando nodos acústicos colaborativos. El prototipo consiste en dos sistemas de control de audio personalizado (PAC) compuestos por un asiento de coche y un nodo acústico, el cual está equipado con dos altavoces, dos micrófonos y un procesador con capacidad de comunicación entre los dos nodos. De esta manera, es posible crear dos zonas independientes de control de ruido que mejoran el confort acústico del usuario sin necesidad de utilizar auriculares.[CA] Aquesta tesi s'emmarca en el camp de les Tecnologies de la Informació i les Comunicacions (TIC), especialment en l'àrea del processament digital del senyal. En l'actualitat, i a causa de l'auge de la Internet dels coses (IoT), existeix un creixent interés per les xarxes de sensors sense fils (WSN), és a dir, xarxes compostes de diferents tipus de dispositius específicament distribuïts en una determinada zona per a fer diferents tasques de processament de senyal. Aquests dispositius o nodes solen estar equipats amb transductors electroacústics així com amb potents i eficients processadors amb capacitat de comunicació. En el cas particular de les xarxes de sensors acústics (ASN), els nodes es dediquen a resoldre diferents tasques de processament de senyals acústics. El desenvolupament de potents sistemes de processament centralitzat han permés augmentar el nombre de canals d'àudio, ampliar l'àrea de control o implementar algorismes més complexos. En la majoria dels casos, una topologia de ASN distribuïda pot ser desitjable a causa de diversos factors tals com el nombre limitat de canals utilitzats pels dispositius d'adquisició i reproducció d'àudio, la conveniència d'un sistema escalable o les altes exigències computacionals dels sistemes centralitzats. Tots aquests aspectes poden portar a la utilització de noves tècniques de processament distribuït de senyals amb la finalitat d'aplicar-les en ASNs. Per a això, una de les principals aportacions d'aquesta tesi és el desenvolupament d'algorismes de filtrat adaptatiu per a sistemes d'àudio multicanal en xarxes distribuïdes. És important tindre en compte que, per a aplicacions de control del camp sonor (SFC), com el control actiu de soroll (ANC) o l'equalització activa de soroll (ANE), els nodes acústics han d'estar equipats amb actuadors amb la finalitat de controlar i modificar el camp sonor. No obstant això, la majoria de les propostes de xarxes distribuïdes adaptatives utilitzades per a resoldre problemes de control del camp sonor no tenen en compte que els nodes poden modificar el comportament de la resta. Per tant, una altra contribució destacable d'aquesta tesi se centra en l'anàlisi de com el sistema acústic afecta el comportament dels nodes dins d'una ASN. En els casos en què l'entorn acústic afecta negativament a l'estabilitat del sistema, s'han proposat diverses estratègies distribuïdes per a resoldre el problema d'interferència acústica amb l'objectiu d'estabilitzar els sistemes de ANC. En el disseny dels algorismes distribuïts també s'han tingut en compte aspectes d'implementació pràctica. A més, amb l'objectiu de crear perfils d'equalització diferents en zones d'escolta independents en presència de sorolls multitonales, s'han presentat diversos algorismes distribuïts de ANE en banda estreta i banda ampla sobre una ASN amb una comunicació col·laborativa i composta per nodes acústics. Es presenten a més resultats experimentals per a validar l'ús dels algorismes distribuïts proposats en el treball per a aplicacions pràctiques. Per a això, s'ha dissenyat un programari de simulació acústica que permet analitzar el rendiment dels algorismes desenvolupats en la tesi. Finalment, s'ha realitzat una implementació pràctica que permet executar aplicacions multicanal de SFC. Per a això, s'ha desenvolupat un prototip en temps real que controla les aplicacions de ANC i ANE utilitzant nodes acústics col·laboratius. El prototip consisteix en dos sistemes de control d'àudio personalitzat (PAC) compostos per un seient de cotxe i un node acústic, el qual està equipat amb dos altaveus, dos micròfons i un processador amb capacitat de comunicació entre els dos nodes. D'aquesta manera, és possible crear dues zones independents de control de soroll que milloren el confort acústic de l'usuari sense necessitat d'utilitzar auriculars.[EN] This thesis fits into the field of Information and Communications Technology (ICT), especially in the area of digital signal processing. Nowadays and due to the rise of the Internet of Things (IoT), there is a growing interest in wireless sensor networks (WSN), that is, networks composed of different types of devices specifically distributed in some area to perform different signal processsing tasks. These devices, also referred to as nodes, are usually equipped with electroacoustic transducers as well as powerful and efficient processors with communication capability. In the particular case of acoustic sensor networks (ASN), nodes are dedicated to solving different acoustic signal processing tasks. These audio signal processing applications have been undergone a major development in recent years due in part to the advances made in computer hardware and software. The development of powerful centralized processing systems has allowed the number of audio channels to be increased, the control area to be extended or more complex algorithmms to be implemented. In most cases, a distributed ASN topology can be desirable due to several factors such as the limited number of channels used by the sound acquisition and reproduction devices, the convenience of a scalable system or the high computational demands of a centralized fashion. All these aspects may lead to the use of novel distributed signal processing techniques with the aim to be applied over ASNs. To this end, one of the main contributions of this dissertation is the development of adaptive filtering algorithms for multichannel sound systems over distributed networks. Note that, for sound field control (SFC) applications, such as active noise control (ANC) or active noise equalization (ANE), acoustic nodes must be not only equipped with sensors but also with actuators in order to control and modify the sound field. However, most of the adaptive distributed networks approaches used to solve soundfield control problems do not take into account that the nodes may interfere or modify the behaviour of the rest. Therefore, other important contribution of this thesis is focused on analyzing how the acoustic system affects the behavior of the nodes within an ASN. In cases where the acoustic environment adversely affects the system stability, several distributed strategies have been proposed for solving the acoustic interference problem with the aim to stabilize ANC control systems. These strategies are based on both collaborative and non-collaborative approaches. Implementation aspects such as hardware constraints, sensor locations, convergenge rate or computational and communication burden, have been also considered on the design of the distributed algorithms. Moreover and with the aim to create independent-zone equalization profiles in the presence of multi-tonal noises, distributed narrowband and broadband ANE algorithms over an ASN with a collaborative learning and composed of acoustic nodes have been presented. Experimental results are presented to validate the use of the distributed algorithms proposed in the work for practical applications. For this purpose, an acoustic simulation software has been specifically designed to analyze the performance of the developed algorithms. Finally, the performance of the proposed distributed algorithms for multichannel SFC applications has been evaluated by means of a real practical implementation. To this end, a real-time prototype that controls both ANC and ANE applications by using collaborative acoustic nodes has been developed. The prototype consists of two personal audio control (PAC) systems composed of a car seat and an acoustic node, which is equipped with two loudspeakers, two microphones and a processor with communications capability. In this way, it is possible to create two independent noise control zones improving the acoustic comfort of the user without the use of headphones.Antoñanzas Manuel, C. (2019). Distributed and Collaborative Processing of Audio Signals: Algorithms, Tools and Applications [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/130209TESISCompendi

An Active Noise Control System Based on Soundfield Interpolation Using a Physics-informed Neural Network

Conventional multiple-point active noise control (ANC) systems require placing error microphones within the region of interest (ROI), inconveniencing users. This paper designs a feasible monitoring microphone arrangement placed outside the ROI, providing a user with more freedom of movement. The soundfield within the ROI is interpolated from the microphone signals using a physics-informed neural network (PINN). PINN exploits the acoustic wave equation to assist soundfield interpolation under a limited number of monitoring microphones, and demonstrates better interpolation performance than the spherical harmonic method in simulations. An ANC system is designed to take advantage of the interpolated signal to reduce noise signal within the ROI. The PINN-assisted ANC system reduces noise more than that of the multiple-point ANC system in simulations

A computationally efficient frequency-domain filtered-X LMS algorithm for virtual microphone

The computational complexity of the virtual FXLMS algorithm is higher than that of the conventional FXLMS algorithm. The additional complexity comes from computation of three secondary path transfer functions (as opposed to one) and a transfer function between the physical and the virtual microphones. The order of these transfer functions may be very high in practical situations where the acoustic damping is low. The high computational complexity of the virtual FXLMS algorithm imposes issues like high power consumption, making it difficult to implement the algorithm in battery operated ANC devices such as active headsets. In addition, the operating sampling frequency of the algorithm is limited and this in turn restricts its operation to relatively low frequency applications. In this paper, a new virtual FXLMS algorithm is derived by implementing all of the secondary path transfer functions in the frequency domain. The algorithm is simulated using measured transfer functions in a duct with low acoustic damping. Implementation schemes are proposed for the new frequency-domain virtual FXLMS algorithm, citing its advantages for use as an efficient real-time active noise control algorithm. © 2013 Elsevier Ltd.Debi Prasad Das, Danielle J. Moreau, Ben S.Cazzolat

H∞ Estimation Approach to Active Noise Control: Theory, Algorithm and Real-Time Implementation

This paper presents an H∞ estimation approach to active control of acoustic noise inside an enclosure. It is shown how H∞ filter theory and algorithm can be effectively applied to active noise control to provide important robustness property. Real-time implementation of the algorithm is performed on Digital Signal Processor. Experimental comparison to conventional FxLMS algorithm for active noise control is presented for both single channel and multichannel cases. While providing some new results, this paper also serves as a brief review on H∞ filter theory and on active noise control

Causality study on a feedforward active noise control headset with different noise coming directions in free field

A systematic analysis is proposed to predict the performance of a typical feedforward single channel ANC headset in terms of the delay, especially the non-causal delay caused by different noise coming directions. First, the performance of a non-causal feedforward system for a band-limited noise is analyzed by using a simplified pure delay model, where it is found that the noise reduction bandwidth is narrowed and the maximum noise reduction is decreased with the increase of the non-causal delay. Second, a systematic method is developed, which can be used to predict the system performance with measured primary and secondary path transfer functions in most practical sound fields and to study the effects of the control filter length and the path delay on the performance. Then, the causality of a typical feedforward active noise control headset with the primary source at 0 and 90 positions in an anechoic chamber is analyzed, and the performance for the two locations predicted by the systematic analysis is shown in good agreements with the experiment results. Finally, an experiment of a typical feedforward active noise control headset in a reverberation chamber is carried out, which shows the validity of the proposed systematic analysis for other more practical sound fields. © 2014 Elsevier Ltd. All rights reserved

Simulation model for an Active Noise Control system : development and validation

Aktiivisen äänenhallintajärjestelmän suunnittelu ja toteutus vaatii akustiikan, mekaniikan ja elektroniikan osaamista. Nykyiset tietokoneet mahdollistavat aktiivisten äänenhallintajärjestelmien simuloinnin, joten on mahdollista sekä säästää suunnittelutyön resursseja että tutkia syvällisemmin järjestelmän riippuvuuksia simulaatiomallien avulla. Järkevin tapa toteuttaa simulaatiomalli riippuu käyttötarkoituksesta ja lähtökohdista. Simulaatiomallin kehittäminen jakautuu kahteen osaan – melun ja vastaäänen mallintamiseen. Melu on mallinnettava, mikäli vaimennettavaa ympäristöä herätteineen ei ole olemassa. Äänenhallintajärjestelmän tuottamaan vastaääntä ei voida simuloida ilman tarkkaa tietoa melusta. Vastaäänen mallintamisessa on mallinnettava säätöjärjestelmä ja sen vuorovaikutus akustisen ympäristön kanssa. Aktiivisen äänenhallinnan sovelluksissa anturit voidaan harvoin sijoittaa kuulijan korvien välittömään läheisyyteen. Tästä syystä on usein hyödyllistä tutkia sitä, miten erilaiset anturi- ja kaiutinpaikat vaikuttavat korvalla kuultavaan ääneen. Tässä diplomityössä mallinnetaan olemassa oleva yksikanavainen myötäkytketty äänenhallintajärjestelmä ja tutkitaan simulaatiomallin ja mittauksen vastaavuutta muuttuvalla meluherätteellä eri tarkkailupisteissä. Simulaatiomalli kehitetään MATLAB Simulink ympäristöön. Säätöjärjestelmänä käytetään digitaalista signaaliprosessoria.Nowadays computers are able to simulate active noise control systems, so it is possible to save costs and research the systems more deeply with simulation models. The development of an ANC simulation model can be divided into two parts: the modelling of primary noise and the modelling of secondary, or counter, noise. The noise made by the ANC system can be modelled only if we have the information of primary noise. For successful simulation of secondary noise, we have to model the control system and its interaction with the surrounding acoustical space. In ANC applications, sensors can seldom be placed near the listeners ears. In that sense, it is valuable to inspect the effect of transducer locations on the total noise at the listener's ears. In this thesis, a simulation model for an ANC system with a one-channel tonal feedforward control system is developed and verified through comparative simulations and measurements in separate observation points. The noise excitation used in the verification phase is tonal and it has dynamic frequency content. The simulation model has been developed in MATLAB Simulink environment. The control system has been coded in a digital signal processor

Analysis and implementation of adaptive filtered-X LMS algorithm based on reference signal self-extraction

By comparing conventional FXLMS (filtered-X least mean square) control algorithms, the present paper introduces an improved adaptive vibration control FXLMS algorithm based on reference signal self-extraction. It overcomes the problem of reference signal which correlated with external excitation signal is needed to be predicted in advance, namely, the reference signal is extracted from structural vibration in real time in the process of control algorithm. Its theoretical basis is: get an original vibration signal estimation using the error signal of the system and the estimation value is taken as the reference signal of adaptive filtering. In addition, to verify the feasibility and advantage of the proposed algorithm, we simulate solar panels with piezoelectric smart flexible plate and construct the corresponding experimental platform. Finally, the results presented in this paper demonstrate that the proposed algorithm is feasible, effective and achieve improvement with significantly faster convergence speed and better control effect compared with other algorithms

Ultra-broadband active noise cancellation at the ears via optical microphones

High frequency noise has generally been difficult to be cancelled actively at a person's ears, particularly for active headrest systems aiming to free the listener from noise cancellation headphones. One of the main challenges is to measure the noise precisely at the ears. Here we demonstrate a new error sensing methodology with an optical microphone arrangement for active noise cancellation (ANC). It can measure the noise accurately for ANC without any obstructions at the listener's ears. The demonstrated system, or virtual ANC headphone as we call it, is shown to provide more than 10 dB attenuation for ultra-broadband noise - up to 6000 Hz - inside the ears in a complex sound field. The bandwidth of the controllable noise significantly exceeds the results from the state-of-the-art system, which is below 1000 Hz. The proposed method leads to the next generation of personal hearing protection system and can open up a whole new area of sound control research