Demo Data from EDBT 2026 / reviewers in the wild / expert
Tim Lübeck
dblp:306/4725
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0003-2870-095XORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing › spatial audio
binaural reproduction |
0.7 | 1 | 2023 | Spatial Upsampling of Sparse Spherical Microphone Array Signals · IEEE ACM Trans. Audio Speech Lang. Process. 2023 |
Audio and music processing
spatial audio |
0.7 | 1 | 2023 | Spatial Upsampling of Sparse Spherical Microphone Array Signals · IEEE ACM Trans. Audio Speech Lang. Process. 2023 |
Audio and music processing › microphone array processing
spherical microphone array processing |
0.7 | 1 | 2023 | Spatial Upsampling of Sparse Spherical Microphone Array Signals · IEEE ACM Trans. Audio Speech Lang. Process. 2023 |
Methods — techniques the papers use, named apart from their topics
spherical harmonics · 0.7magnitude least-squares optimization · 0.7cross-correlation · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Spatial Upsampling of Sparse Spherical Microphone Array SignalsabstractWe present a method for spatial upsampling of signals captured with spherical microphone arrays with a limited number of microphones. The upsampling is performed by adding virtual microphone signals using interpolation between the measured array signals. For interpolation, the differences in amplitude and time of neighbored signals are weighted separately. For this, the time differences are determined with a broadband cross-correlation. After the upsampling, the array signals can be represented as spherical harmonics (SH) coefficients at significantly higher orders. This work introduces the proposed upsampling procedure and presents a technical evaluation based on simulated and measured sound fields. Thereby, we focus on the binaural decoding of the upsampled SH signals. For perceptual evaluation, we present the results of a listening experiment evaluating the binaural reproduction of the upsampled signals compared to a baseline Ambisonics decoding and the state-of-the-art decoding with Magnitude Least-Squares optimization. Both the technical and perceptual evaluations consider only array impulse responses, but the algorithm could generally be applied to array streams. The evaluation shows that the proposed method significantly improves the binaural reproduction of low-order spherical microphone array captures compared to established methods. Tim Lübeck, Johannes M. Arend, Christoph Pörschmann |
IEEE ACM Trans. Audio Speech Lang. Process. | 1 |