Μοdelling, analysis, and processing of room responses and reverberant signals
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Date
2014-05-16
Authors
Γεωργαντή, Ελευθερία
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Abstract
The main focus of this thesis is to analyse signals (signal-dependent analysis) and room responses (system-dependent analysis) from a statistical point of view, attempt to determine the underlying statistical relationships between the reverberant signals and the room responses and propose relevant statistical models. Based on such a statistical framework, this thesis aims to propose novel methodologies for the extraction of room acoustical information and parameters from reverberant signals. Schroeder's theory is experimentally evaluated for various Room Transfer Functions (RTFs) measured in many source/receiver positions in various enclosures and several related aspects are discussed. Using a statistical approach, the effects of reverberant energy on the histograms and statistical measures are discussed and models describing the relationship of statistical measures between the reverberant signal and the RTFs are extracted. Then, the statistical properties of Binaural Room Transfer Functions (BRTFs) and binaural cues are examined. The well-known property of the spectral standard deviation of the magnitude of RTFs, that is its convergence to 5.6 dB for diffuse fields, is examined for the case of BRTFs, using a similar approach and a generic model for the relationship of the spectral standard deviation of RTFs and BRTFs.
This thesis is also concerned with the distance estimation problem from a perceptual and computational point of view. Two novel methods for the estimation of the source/receiver distance using speech signals are proposed. The first method is able to detect the distance between the speaker and the microphone in a room environment using single-channel signals. The distance-dependent variation of several temporal and spectral statistical features of single-channel signals is studied and a novel sound source distance detector, based on these features is developed. The second method estimates distance from binaural speech signals (two-channel signals). This method does not require a priori knowledge of the room impulse response, the reverberation time or any other acoustical parameter and relies on a set of novel features extracted from the reverberant binaural signals. For this method, a novel distance estimation feature is introduced exploiting the standard deviation of the difference of the magnitude spectra of the left and right binaural signals (termed here as Binaural Spectral Magnitude Difference Standard Deviation (BSMD STD)). Moreover, an extended and novel set of additional features based on the statistical properties of binaural cues (ILDs, ITDs, ICs) is extracted from an auditory front-end which models the peripheral processing of the human auditory system. Both methods rely on novel distance-dependent features, related to statistical parameters of speech signals.
Finally, a novel method for the estimation of the direct-to-reverberant-ratio (DRR) from dual-channel microphone recordings without having knowledge of the source signal is presented.
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Keywords
Room acoustics, Room impulse response, Reverberation, Distance estimation, Direct-to-reverberant-ratio, Binaural room impulse response, Room transfer function model, Statistical analysis