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

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    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

    DoubleEcho: Mitigating Context-Manipulation Attacks in Copresence Verification

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    Copresence verification based on context can improve usability and strengthen security of many authentication and access control systems. By sensing and comparing their surroundings, two or more devices can tell whether they are copresent and use this information to make access control decisions. To the best of our knowledge, all context-based copresence verification mechanisms to date are susceptible to context-manipulation attacks. In such attacks, a distributed adversary replicates the same context at the (different) locations of the victim devices, and induces them to believe that they are copresent. In this paper we propose DoubleEcho, a context-based copresence verification technique that leverages acoustic Room Impulse Response (RIR) to mitigate context-manipulation attacks. In DoubleEcho, one device emits a wide-band audible chirp and all participating devices record reflections of the chirp from the surrounding environment. Since RIR is, by its very nature, dependent on the physical surroundings, it constitutes a unique location signature that is hard for an adversary to replicate. We evaluate DoubleEcho by collecting RIR data with various mobile devices and in a range of different locations. We show that DoubleEcho mitigates context-manipulation attacks whereas all other approaches to date are entirely vulnerable to such attacks. DoubleEcho detects copresence (or lack thereof) in roughly 2 seconds and works on commodity devices

    Effects of errorless learning on the acquisition of velopharyngeal movement control

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    Session 1pSC - Speech Communication: Cross-Linguistic Studies of Speech Sound Learning of the Languages of Hong Kong (Poster Session)The implicit motor learning literature suggests a benefit for learning if errors are minimized during practice. This study investigated whether the same principle holds for learning velopharyngeal movement control. Normal speaking participants learned to produce hypernasal speech in either an errorless learning condition (in which the possibility for errors was limited) or an errorful learning condition (in which the possibility for errors was not limited). Nasality level of the participants’ speech was measured by nasometer and reflected by nasalance scores (in %). Errorless learners practiced producing hypernasal speech with a threshold nasalance score of 10% at the beginning, which gradually increased to a threshold of 50% at the end. The same set of threshold targets were presented to errorful learners but in a reversed order. Errors were defined by the proportion of speech with a nasalance score below the threshold. The results showed that, relative to errorful learners, errorless learners displayed fewer errors (50.7% vs. 17.7%) and a higher mean nasalance score (31.3% vs. 46.7%) during the acquisition phase. Furthermore, errorless learners outperformed errorful learners in both retention and novel transfer tests. Acknowledgment: Supported by The University of Hong Kong Strategic Research Theme for Sciences of Learning © 2012 Acoustical Society of Americapublished_or_final_versio

    Control Effort Strategies for Acoustically Coupled Distributed Acoustic Nodes

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    [EN] This paper considers the effect of effort constraints on the behavior of an active noise control (ANC) system over a distributed network composed of acoustic nodes. A distributed implementation can be desirable in order to provide more flexible, versatile, and scalable ANC systems. In this regard, the distributed version of the multiple error filtered-x least mean square (DMEFxLMS) algorithm that allows collaboration between nodes has shown excellent properties. However, practical constraints need to be considered since, in real scenarios, the acoustic nodes are equipped with power constrained actuators. If these constraints are not considered within the adaptive algorithm, the control signals may increase and saturate the hardware devices, causing system instability. To avoid this drawback, a control effort weighting can be considered in the cost function of the distributed algorithm at each node. Therefore, a control effort strategy over the output signals at each node is used to keep them under a given threshold and ensuring the distributed ANC system stability. Experimental results show that, assuming ideal network communications, the proposed distributed algorithm achieves the same performance as the leaky centralized ANC system. A performance evaluation of several versions of the leaky DMEFxLMS algorithm in realistic scenarios is also included.This work has been supported by European Union ERDF together with Spanish Government through TEC2015-67387-C4-1-R project and Generalitat Valenciana through PROMETEOII/2014/003 project.Antoñanzas-Manuel, C.; Ferrer Contreras, M.; Diego Antón, MD.; Gonzalez, A. (2017). Control Effort Strategies for Acoustically Coupled Distributed Acoustic Nodes. Wireless Communications and Mobile Computing. 2017:1-15. https://doi.org/10.1155/2017/3601802S1152017Akyildiz, I. F., Weilian Su, Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine, 40(8), 102-114. doi:10.1109/mcom.2002.1024422Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292-2330. doi:10.1016/j.comnet.2008.04.002Puccinelli, D., & Haenggi, M. (2005). Wireless sensor networks: applications and challenges of ubiquitous sensing. IEEE Circuits and Systems Magazine, 5(3), 19-31. doi:10.1109/mcas.2005.1507522Xiaojiang Du, & Hsiao-Hwa Chen. (2008). Security in wireless sensor networks. IEEE Wireless Communications, 15(4), 60-66. doi:10.1109/mwc.2008.4599222Al Ameen, M., Liu, J., & Kwak, K. (2010). Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications. Journal of Medical Systems, 36(1), 93-101. doi:10.1007/s10916-010-9449-4Martinez, K., Hart, J. K., & Ong, R. (2004). Environmental sensor networks. Computer, 37(8), 50-56. doi:10.1109/mc.2004.91Segura-Garcia, J., Felici-Castell, S., Perez-Solano, J. J., Cobos, M., & Navarro, J. M. (2015). Low-Cost Alternatives for Urban Noise Nuisance Monitoring Using Wireless Sensor Networks. IEEE Sensors Journal, 15(2), 836-844. doi:10.1109/jsen.2014.2356342Flammini, A., Ferrari, P., Marioli, D., Sisinni, E., & Taroni, A. (2009). Wired and wireless sensor networks for industrial applications. Microelectronics Journal, 40(9), 1322-1336. doi:10.1016/j.mejo.2008.08.012Lopes, C. G., & Sayed, A. H. (2007). Incremental Adaptive Strategies Over Distributed Networks. IEEE Transactions on Signal Processing, 55(8), 4064-4077. doi:10.1109/tsp.2007.896034Cobos, M., Perez-Solano, J. J., Belmonte, O., Ramos, G., & Torres, A. M. (2016). Simultaneous Ranging and Self-Positioning in Unsynchronized Wireless Acoustic Sensor Networks. IEEE Transactions on Signal Processing, 64(22), 5993-6004. doi:10.1109/tsp.2016.2603972Llerena-Aguilar, C., Gil-Pita, R., Rosa-Zurera, M., Ayllón, D., Utrilla-Manso, M., & Llerena, F. (2016). Synchronization based on mixture alignment for sound source separation in wireless acoustic sensor networks. Signal Processing, 118, 177-187. doi:10.1016/j.sigpro.2015.06.023Elliott, S. J., & Nelson, P. A. (1993). Active noise control. IEEE Signal Processing Magazine, 10(4), 12-35. doi:10.1109/79.248551Elliott, S. J., Joseph, P., Bullmore, A. J., & Nelson, P. A. (1988). Active cancellation at a point in a pure tone diffuse sound field. Journal of Sound and Vibration, 120(1), 183-189. doi:10.1016/0022-460x(88)90343-4Joseph, P., Elliott, S. J., & Nelson, P. A. (1994). Near Field Zones of Quiet. Journal of Sound and Vibration, 172(5), 605-627. doi:10.1006/jsvi.1994.1202Kuo, S. M., & Morgan, D. R. (1999). Active noise control: a tutorial review. Proceedings of the IEEE, 87(6), 943-975. doi:10.1109/5.763310Burgess, J. C. (1981). Active adaptive sound control in a duct: A computer simulation. The Journal of the Acoustical Society of America, 70(3), 715-726. doi:10.1121/1.386908Elliott, S. J., & Boucher, C. C. (1994). Interaction between multiple feedforward active control systems. IEEE Transactions on Speech and Audio Processing, 2(4), 521-530. doi:10.1109/89.326611Grosdidier, P., & Morari, M. (1986). Interaction measures for systems under decentralized control. Automatica, 22(3), 309-319. doi:10.1016/0005-1098(86)90029-4Elliott, S., Stothers, I., & Nelson, P. (1987). A multiple error LMS algorithm and its application to the active control of sound and vibration. IEEE Transactions on Acoustics, Speech, and Signal Processing, 35(10), 1423-1434. doi:10.1109/tassp.1987.1165044Elliott, S. J., & Back, K. H. (1996). Effort constraints in adaptive feedforward control. IEEE Signal Processing Letters, 3(1), 7-9. doi:10.1109/97.475821Qiu, X., & Hansen, C. H. (2001). A study of time-domain FXLMS algorithms with control output constraint. The Journal of the Acoustical Society of America, 109(6), 2815-2823. doi:10.1121/1.1367247Rafaely, B., & Elliot, S. J. (2000). A computationally efficient frequency-domain LMS algorithm with constraints on the adaptive filter. IEEE Transactions on Signal Processing, 48(6), 1649-1655. doi:10.1109/78.845922Kozacky, W. J., & Ogunfunmi, T. (2013). An active noise control algorithm with gain and power constraints on the adaptive filter. EURASIP Journal on Advances in Signal Processing, 2013(1). doi:10.1186/1687-6180-2013-17Mosquera-Sánchez, J. A., Desmet, W., & de Oliveira, L. P. R. (2017). A multichannel amplitude and relative-phase controller for active sound quality control. Mechanical Systems and Signal Processing, 88, 145-165. doi:10.1016/j.ymssp.2016.10.036Rossetti, D. J., Jolly, M. R., & Southward, S. C. (1996). Control effort weighting in feedforward adaptive control systems. The Journal of the Acoustical Society of America, 99(5), 2955-2964. doi:10.1121/1.414877Antoñanzas, C., Ferrer, M., de Diego, M., & Gonzalez, A. (2016). Blockwise Frequency Domain Active Noise Controller Over Distributed Networks. Applied Sciences, 6(5), 124. doi:10.3390/app605012

    Sonic Interactions in Virtual Environments

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    This open access book tackles the design of 3D spatial interactions in an audio-centered and audio-first perspective, providing the fundamental notions related to the creation and evaluation of immersive sonic experiences. The key elements that enhance the sensation of place in a virtual environment (VE) are: Immersive audio: the computational aspects of the acoustical-space properties of Virutal Reality (VR) technologies Sonic interaction: the human-computer interplay through auditory feedback in VE VR systems: naturally support multimodal integration, impacting different application domains Sonic Interactions in Virtual Environments will feature state-of-the-art research on real-time auralization, sonic interaction design in VR, quality of the experience in multimodal scenarios, and applications. Contributors and editors include interdisciplinary experts from the fields of computer science, engineering, acoustics, psychology, design, humanities, and beyond. Their mission is to shape an emerging new field of study at the intersection of sonic interaction design and immersive media, embracing an archipelago of existing research spread in different audio communities and to increase among the VR communities, researchers, and practitioners, the awareness of the importance of sonic elements when designing immersive environments

    Sonic interactions in virtual environments

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    This book tackles the design of 3D spatial interactions in an audio-centered and audio-first perspective, providing the fundamental notions related to the creation and evaluation of immersive sonic experiences. The key elements that enhance the sensation of place in a virtual environment (VE) are: Immersive audio: the computational aspects of the acoustical-space properties of Virutal Reality (VR) technologies Sonic interaction: the human-computer interplay through auditory feedback in VE VR systems: naturally support multimodal integration, impacting different application domains Sonic Interactions in Virtual Environments will feature state-of-the-art research on real-time auralization, sonic interaction design in VR, quality of the experience in multimodal scenarios, and applications. Contributors and editors include interdisciplinary experts from the fields of computer science, engineering, acoustics, psychology, design, humanities, and beyond. Their mission is to shape an emerging new field of study at the intersection of sonic interaction design and immersive media, embracing an archipelago of existing research spread in different audio communities and to increase among the VR communities, researchers, and practitioners, the awareness of the importance of sonic elements when designing immersive environments

    Sonic Interactions in Virtual Environments

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