20 citations · 93 across the 19 of their papers we have counts for
3 papers · 1 filter
Bespoke Neural Networks for Score-Informed Source Separation
Ethan Manilow, Bryan Pardo
In this paper, we introduce a simple method that can separate arbitrary musical instruments from an audio mixture. Given an unaligned MIDI transcription for a target instrument fro…
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…