Browsing by Author "Waterschoot, Toon van"

Now showing 1 - 3 of 3
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    Fast Low-Latency Convolution by Low-Rank Tensor Approximation
    (2023-06-10) Jälmby, Martin; Elvander, Filip; Waterschoot, Toon van; Brno University of Technology; Department of Information and Communications Engineering; Department of Information and Communications Engineering
    In this paper we consider fast time-domain convolution, exploiting low-rank properties of an impulse response (IR). This reduces the computational complexity, speeding up the convolution, without introducing latency. Previous work has considered a truncated singular value decomposition (SVD) of a two-dimensional matricization, or reshaping, of the IR. We here build upon this idea, by providing an algorithm for convolution with a three-dimensional tensorization of the IR. We provide simulations using real-life acoustic room impulse responses (RIRs) of various lengths, convolving them with music, as well as speech signals. The proposed algorithm is shown to outperform the comparable existing algorithm in terms of signal quality degradation, for all considered scenarios, without increasing the computational complexity, or the memory usage.
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    Multi-Source Direction-of-Arrival Estimation Using Steered Response Power and Group-Sparse Optimization
    (IEEE, 2024) Tengan, Elisa; Dietzen, Thomas; Elvander, Filip; Waterschoot, Toon van; Department of Information and Communications Engineering; Structured and Stochastic Modeling; KU Leuven
    In this paper, a method is proposed for estimating the direction of arrival (DOA) of multiple broadband sound sources. This is achieved through the solution of a group-sparse optimization problem, which models an observed broadband steered response power (SRP) map as a linear function of power spectral densities (PSDs), corresponding to a set of candidate DOAs, and forming a PSD vector. Given the assumption of spatial sparsity, the estimation of the source DOAs is then accomplished by identifying peaks in the resulting spatial power density, i.e., the estimated direction-specific PSDs integrated over frequency. The motivation behind the proposed method lies in its potential to reveal more distinct peaks in the estimated spatial power density than those directly observed in the broadband SRP map, which can be beneficial to the robustness in DOA estimation performance when multiple sources need to be distinguished under varying acoustic conditions. An implementation of the proposed method using the alternating direction method of multipliers (ADMM) is presented, and the DOA estimation performance is evaluated with both simulated and experimental data. Results show that, especially in reverberant scenarios, the proposed method presents an advantage in locating closely spaced sources when compared to the conventional SRP-PHAT, the group-sparse iterative covariance-based estimation (GSPICE) method, and the wideband MUSIC method with geometric averaging. Furthermore, it is observed that for a compact microphone array, the proposed method overall maintained its performance even when using SRP maps computed with grid resolutions that are lower than the sampling requirements of the broadband SRP function. Finally, results obtained with experimental data showed the validity and applicability of the proposed method in a practical meeting room environment.
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    Simultaneous Acoustic Echo Sorting and 3-D Room Geometry Inference
    (2023-06-10) MacWilliam, Kathleen; Elvander, Filip; Waterschoot, Toon van; KU Leuven; Structured and Stochastic Modeling; Department of Information and Communications Engineering
    Room geometry estimation from multiple acoustic room impulse responses (RIRs) relies on being able to correctly identify first-order echoes corresponding to the same reflector. This can be done by exploiting the properties of various mathematical concepts but often results in needing to solve large combinatorial problems owing to the increased number of measurements these tools require for efficacy. A low-complexity iterative method is proposed for determining the boundaries in convex polygonal rooms using common tangent planes to sets of ellipsoids. Prior knowledge of the order of echoes is unnecessary and only three RIRs are required, which is one less than the minimum number typically needed to find a unique reflector in 3-D, allowing for simpler common tangent plane estimation and reducing possible echo combinations. Candidate partial rooms are built by checking whether expected second-order echoes appear in the RIRs, adding a reflector at each iterate until a room is found. The proposed method is validated by means of computer simulations.