Wireless acoustic sensor networks (WASNs) are formed by a distributed group of acoustic-sensing devices featuring audio playing and recording capabilities. Current mobile computing platforms offer great possibilities for the design of audio-related applications involving acoustic-sensing nodes. In this context, acoustic source localization is one of the application domains that have attracted the most attention of the research community along the last decades. In general terms, the localization of acoustic sources can be achieved by studying energy and temporal and/or directional features from the incoming sound at different microphones and using a suitable model that relates those features with the spatial location of the source (or sources) of interest. This paper reviews common approaches for source localization in WASNs that are focused on different types of acoustic features, namely, the energy of the incoming signals, their time of arrival (TOA) or time difference of arrival (TDOA), the direction of arrival (DOA), and the steered response power (SRP) resulting from combining multiple microphone signals. Additionally, we discuss methods not only aimed at localizing acoustic sources but also designed to locate the nodes themselves in the network. Finally, we discuss current challenges and frontiers in this field.
In this work, we consider the data-association problem for the localization of multiple sound sources in a wireless acoustic sensor network (WASN), where each node is a microphone array, using direction of arrival (DOA) estimates. The data-association problem arises because the central node that receives the multiple DOA estimates from the nodes cannot know to which source they belong. Hence, the DOAs from the different nodes that correspond to the same source must be found in order to perform accurate localization. We present a method to identify the correct association of DOAs to the sources and thus accurately estimate their locations. Our method results in high association and localization accuracy in realistic scenarios with missed detections, reverberation, noise, and moving sources and outperforms other recently proposed methods. It also incorporates a bitrate reduction scheme in order to keep the amount of information that needs to be transmitted in the network at low levels without affecting performance.
We propose a real-time method for coding an acoustic environment based on estimating the Direction-of-Arrival (DOA) and reproducing it using an arbitrary loudspeaker configuration or headphones. We encode the sound field with the use of one audio signal and side-information. The audio signal can be further encoded with an MP3 encoder to reduce the bitrate. We investigate how such coding can affect the spatial impression and sound quality of spatial audio reproduction. Also, we propose a lossless efficient compression scheme for the side-information. Our method is compared with other recently proposed microphone array based methods for directional coding. Listening tests confirm the effectiveness of our method in achieving excellent reconstruction of the sound field while maintaining the sound quality at high levels.
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