Demo Data from SIGIR 2026 / reviewers in the wild / expert
Lukas Grinewitschus
dblp:304/8227
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-6028-3781ORCID · 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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing › music transcription
multipitch estimation |
0.6 | 1 | 2022 | The Harmonic Shift Algorithm for Efficient Multi-Pitch Detection · IEEE ACM Trans. Audio Speech Lang. Process. 2022 |
Audio and music processing › time-frequency analysis
constant-q transform |
0.2 | 1 | 2022 | The Harmonic Shift Algorithm for Efficient Multi-Pitch Detection · IEEE ACM Trans. Audio Speech Lang. Process. 2022 |
Methods — techniques the papers use, named apart from their topics
noncoherent blind detection · 0.6constant-q transform · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | The Harmonic Shift Algorithm for Efficient Multi-Pitch DetectionabstractExisting approaches for multi-pitch detection have still been highly complex. In this paper, the harmonic shift algorithm (HSA) for multi-pitch detection is illustrated. The HSA is a noncoherent blind detection scheme, exploiting the constant-Q transform (CQT). The only requirement for the successful application of the HSA is that all the sources are harmonic sources. Due to this simplicity, the HSA is considered viable for both single-pitch and multi-pitch detection, making its attractive for the application in other areas of signal processing. When illustrating the performance capabilities of the HSA, we demonstrate that it outperforms the state of the art regarding the computational complexity providing detection precision, accuracy and a recall factor comparable with existing schemes. Lukas Grinewitschus, Peter Jung 0002 |
IEEE ACM Trans. Audio Speech Lang. Process. | 1 |