From the 1 of 9 linked papers with an AI index.
9 papers
RealDESED: A Real-World Domestic Sound Event Detection Benchmark
Florian Schmid, Paul Primus, Alexander Fichtinger +3
This paper presents RealDESED, a real-world domestic sound event detection (SED) benchmark comprising 5,710 audio recordings collected by 652 participants in their homes. Each reco…
Low-Latency Neural Models for Real-Time Music Enhancement
Emmanouil Karystinaios, Jonathan Greif, David Nadrchal +2
The paper benchmarks compact causal neural networks for real-time music enhancement, analyzing their performance under low‑latency constraints and various degradation types.
Sound Event Detection with Boundary-Aware Optimization and Inference
Florian Schmid, Chi Ian Tang, Sanjeel Parekh +9
Temporal detection problems appear in many fields including time-series estimation, activity recognition and sound event detection (SED). In this work, we propose a new approach to…
Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge
Florian Schmid, Paul Primus, Toni Heittola +3
This paper presents the Low-Complexity Acoustic Scene Classification with Device Information Task of the DCASE 2025 Challenge, along with its baseline system. Continuing the focus…
Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation
Alexander Fichtinger, Jan Schlüter, Gerhard Widmer
Generative models of music audio are typically used to generate output based solely on a text prompt or melody. Boomerang sampling, recently proposed for the image domain, allows g…
Exploring Performance-Complexity Trade-Offs in Sound Event Detection Models
Tobias Morocutti, Florian Schmid, Jonathan Greif +2
We target the problem of developing new low-complexity networks for the sound event detection task. Our goal is to meticulously analyze the performance-complexity trade-off, aiming…