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

Abstract

This thesis fits into the field of Information and Communications Technology (ICT), especially in the area of digital signal processing. Nowadays and due in part 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 processing tasks. These devices, also referred to as nodes, are usually equipped with electroacoustic transducers, such as sensors or actuators, 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, such as environmental sound monitoring, immersive audio, binaural hearing aids, noise-cancelling systems as well as audio teleconferencing. 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. This has led to the development of powerful centralized processing systems that allow the number of audio channels to be increased, the control area to be extended or more complex algorithmms to be implemented, thereby improving audio quality or creating independent control over several personal sound zones. 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. This is an important issue which is tackled throughout this thesis. Therefore, other important contribution of this thesis is focused on analyzing