221 citations · 1k across the 103 of their papers we have counts for
12 papers · 1 filter
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping
Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh +1
Deep Neural Networks are known to be very demanding in terms of computing and memory requirements. Due to the ever increasing use of embedded systems and mobile devices with a limi…
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples
Paul Primus, Verena Haunschmid, Patrick Praher +1
Unsupervised anomalous sound detection is concerned with identifying sounds that deviate from what is defined as 'normal', without explicitly specifying the types of anomalies. A s…
Addressing the Recitative Problem in Real-time Opera Tracking
Charles Brazier, Gerhard Widmer
Robust real-time opera tracking (score following) would be extremely useful for many processes surrounding live opera staging and streaming, including automatic lyrics displays, ca…
audioLIME: Listenable Explanations Using Source Separation
Verena Haunschmid, Ethan Manilow, Gerhard Widmer
Deep neural networks (DNNs) are successfully applied in a wide variety of music information retrieval (MIR) tasks but their predictions are usually not interpretable. We propose au…
Towards Musically Meaningful Explanations Using Source Separation
Verena Haunschmid, Ethan Manilow, Gerhard Widmer
Deep neural networks (DNNs) are successfully applied in a wide variety of music information retrieval (MIR) tasks. Such models are usually considered "black boxes", meaning that th…
The Impact of Label Noise on a Music Tagger
Katharina Prinz, Arthur Flexer, Gerhard Widmer
We explore how much can be learned from noisy labels in audio music tagging. Our experiments show that carefully annotated labels result in highest figures of merit, but even high…