EU Directive 49/2002 and Spanish law 37/2006 urge cities to develop strategic noise maps and action plans to evaluate noise exposure and to establish noise abatement procedures in critical areas. However, noise mapping involves costly and cumbersome measurement procedures that can become a real issue in practice. This paper describes a distributed noise monitoring system based on WASN (Wireless Acoustic Sensor Network) and the application of a geo-statistical methodology for statistical spatial-temporal prediction of noise levels in semi-open areas, such as a typical, small Mediterranean city (Algemesí, València, Spain). This methodology is applied to the study of the spatial evolution in time of the noise pollution. To this end, a spatial statistical model is developed by using the noise pollution measurements obtained over a set of points located at some strategic locations. The geo-statistical time model allows for estimating specific noise levels and characterizing the spatial-temporal variation of the noise pollution. The results show that the developed model provides a good approximation of the measurements obtained experimentally.
This thesis is related to the field of Sound Source Separation (SSS). It addresses the development and evaluation of these techniques for their application in the resynthesis of high-realism sound scenes by means of Wave Field Synthesis (WFS). Because the vast majority of audio recordings are preserved in two-channel stereo format, special up-converters are required to use advanced spatial audio reproduction formats, such as WFS. This is due to the fact that WFS needs the original source signals to be available, in order to accurately synthesize the acoustic field inside an extended listening area. Thus, an object-based mixing is required.Source separation problems in digital signal processing are those in which several signals have been mixed together and the objective is to find out what the original signals were. Therefore, SSS algorithms can be applied to existing two-channel mixtures to extract the different objects that compose the stereo scene. Unfortunately, most stereo mixtures are underdetermined, i.e., there are more sound sources than audio channels. This condition makes the SSS problem especially difficult and stronger assumptions have to be taken, often related to the sparsity of the sources under some signal transformation.This thesis is focused on the application of SSS techniques to the spatial sound reproduction field. As a result, its contributions can be categorized within these two areas. First, two underdetermined SSS methods are proposed to deal efficiently with the separation of stereo sound mixtures. These techniques are based on a multi-level thresholding segmentation approach, which enables to perform a fast and unsupervised separation of sound sources in the time-frequency domain. Although both techniques rely on the same clustering type, the features considered by each of them are related to different localization cues that enable to perform separation of either instantaneous or real mixtures. Additionally, two post-processing techniques aimed at improving the isolation of the separated sources are proposed. The performance achieved by several SSS methods in the resynthesis of WFS sound scenes is afterwards evaluated by means of listening tests, paying special attention to the change observed in the perceived spatial attributes. Although the estimated sources are distorted versions of the original ones, the masking effects involved in their spatial remixing make artifacts less perceptible, which improves the overall assessed quality. Finally, some novel developments related to the application of time-frequency processing to source localization and enhanced sound reproduction are presented.Keywords: Wave Field Synthesis, Sound Source Separation, Time Frequency Processing, Direction of Arrival, Spatial Audio Quality. ResumenEsta tesis se enmarca dentro del campo de la Separación de Fuentes Sonoras (SSS), donde se ha trabajado en el desarrollo y evaluación de estas técnicas para aplicarlas a la resíntesis de escenas sonoras de alto realismo utilizando Síntesis de Campo de Ondas...
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