Regression and Classification for Direction-of-Arrival Estimation with Convolutional Recurrent Neural Networks

We present a novel learning-based approach to estimate the direction-of-arrival (DOA) of a sound source using a convolutional recurrent neural network (CRNN) trained via regression on synthetic data and Cartesian labels. We also describe an improved method to generate synthetic data to train the neural network using state-of-the-art sound propagation algorithms that model specular as well as diffuse reflections of sound. We compare our model against three other CRNNs trained using different formulations of the same problem: classification on categorical labels, and regression on spherical coordinate labels. In practice, our model achieves up to 43% decrease in angular error over prior methods. The use of diffuse reflection results in 34% and 41% reduction in angular prediction errors on LOCATA and SOFA datasets, respectively, over prior methods based on image-source methods. Our method results in an additional 3% error reduction over prior schemes that use classification based networks, and we use 36% fewer network parameters

Polarimetric distance-dependent models for large hall scenarios

A comprehensive polarimetric distance-dependent model of the power delay profile (PDP) and path gain is proposed. The model includes both specular multipath components (SMCs) and dense multipath components (DMC), the latter being modeled with an exponential and power law. The parameters of the model were estimated from polarimetric measurements of a large hall radio channel under line-of-sight (LOS) conditions at 1.3 GHz with a dedicated procedure. The validity and robustness of the proposed approach are provided by the good agreement between the polarimetric data and models for the investigated transmitter-receiver distance range. Furthermore, the description of the radio channel with path loss models is discussed for cases where the DMC is included, and a two-step method to compute the path loss characteristics directly from the measured data is developed. The results of this contribution highlight the fact that a complete polarimetric description of all propagation mechanisms and related path loss models is desired to design faithful polarimetric radio channel models

Physical-statistical modeling of dynamic indoor power delay profiles

This paper presents a physical-statistical radio channel power delay profiles model for room-to-room communication systems combining the room electromagnetic theory for modeling deterministic channel components with a geometry-based stochastic channel model with time-variant statistics for modeling stochastic components. The deterministic channel component, i.e., mean power delay spectrum, is comprised of specularly reflected paths plus diffuse components due to scattering and diffraction. The specular components are modeled with a set Dirac function, whereas the diffuse components modeling approach is a room electromagnetic theory-based model. Dynamic indoor communication channels are characterized by a non-stationary time-and delay-fading process due to changes in the environment. We analyze and model the time-delay variability of channels using K-factor for small-scale variations and the t-location scale distribution parameters for large-scale variations. It turns out that these parameters cannot be assumed to be constant in time and delay. After modeling of time-delay variations of the first order statistics, we generate channel realizations with appropriate second order statistics. As the result, the presented model enables to describe the evolution of the power delay profile in the time domain

Comparative evaluation of predicted and measured performance of a 68-cubic meter truncated reverberant noise chamber

The performance of a medium size, truncated reverberation chamber is evaluated in detail. Chamber performance parameters are predicted, using classical acoustic theory, and are compared to results from actual chamber measurements. Discrepancies are discussed in relation to several available empirical corrections developed by other researchers. Of more practical interest is the confirmation of a recent theory stating that the present guide for the ratio of specimen volume to test chamber volume, approximately 10 percent, is overly conservative, and can be increased by a factor of at least 2 and possibly 3. Results and theoretical justification of these findings are presented

Blind MultiChannel Identification and Equalization for Dereverberation and Noise Reduction based on Convolutive Transfer Function

This paper addresses the problems of blind channel identification and multichannel equalization for speech dereverberation and noise reduction. The time-domain cross-relation method is not suitable for blind room impulse response identification, due to the near-common zeros of the long impulse responses. We extend the cross-relation method to the short-time Fourier transform (STFT) domain, in which the time-domain impulse responses are approximately represented by the convolutive transfer functions (CTFs) with much less coefficients. The CTFs suffer from the common zeros caused by the oversampled STFT. We propose to identify CTFs based on the STFT with the oversampled signals and the critical sampled CTFs, which is a good compromise between the frequency aliasing of the signals and the common zeros problem of CTFs. In addition, a normalization of the CTFs is proposed to remove the gain ambiguity across sub-bands. In the STFT domain, the identified CTFs is used for multichannel equalization, in which the sparsity of speech signals is exploited. We propose to perform inverse filtering by minimizing the $\ell_1$-norm of the source signal with the relaxed $\ell_2$-norm fitting error between the micophone signals and the convolution of the estimated source signal and the CTFs used as a constraint. This method is advantageous in that the noise can be reduced by relaxing the $\ell_2$-norm to a tolerance corresponding to the noise power, and the tolerance can be automatically set. The experiments confirm the efficiency of the proposed method even under conditions with high reverberation levels and intense noise.Comment: 13 pages, 5 figures, 5 table