Search Results for author:
Found 9 papers, 5 papers with code
Differentiable Dictionary Search: Integrating Linear Mixing with Deep Non-Linear Modelling for Audio Source Separation
This paper describes several improvements to a new method for signal decomposition that we recently formulated under the name of Differentiable Dictionary Search (DDS).
Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries
We introduce a novel way to incorporate prior information into (semi-) supervised non-negative matrix factorization, which we call differentiable dictionary search.
Nonlinear Denoising, Linear Demixing
We cast the combinatorial problem of polyphonic piano transcription as a two stage process.
Learning to Read and Follow Music in Complete Score Sheet Images
This paper addresses the task of score following in sheet music given as unprocessed images.
Audio-Conditioned U-Net for Position Estimation in Full Sheet Images
The goal of score following is to track a musical performance, usually in the form of audio, in a corresponding score representation.
Learning to Transcribe by Ear
Within this conceptual framework, the transcription process can be described as the agent interacting with the instrument in the environment, and obtaining reward by playing along with what it hears.
Investigating Label Noise Sensitivity of Convolutional Neural Networks for Fine Grained Audio Signal Labelling
We measure the effect of small amounts of systematic and random label noise caused by slightly misaligned ground truth labels in a fine grained audio signal labeling task.
On the Potential of Simple Framewise Approaches to Piano Transcription
In an attempt at exploring the limitations of simple approaches to the task of piano transcription (as usually defined in MIR), we conduct an in-depth analysis of neural network-based framewise transcription.
Deep Linear Discriminant Analysis
The central idea of this paper is to put LDA on top of a deep neural network.
