66 citations · 244 across the 18 of their papers we have counts for
5 papers · 1 filter
Attention as a Perspective for Learning Tempo-invariant Audio Queries
Matthias Dorfer, Jan Hajič, Gerhard Widmer
Current models for audio--sheet music retrieval via multimodal embedding space learning use convolutional neural networks with a fixed-size window for the input audio. Depending on…
A Hybrid Approach with Multi-channel I-Vectors and Convolutional Neural Networks for Acoustic Scene Classification
Hamid Eghbal-zadeh, Bernhard Lehner, Matthias Dorfer +1
In Acoustic Scene Classification (ASC) two major approaches have been followed . While one utilizes engineered features such as mel-frequency-cepstral-coefficients (MFCCs), the oth…
On the Potential of Simple Framewise Approaches to Piano Transcription
Rainer Kelz, Matthias Dorfer, Filip Korzeniowski +3
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-ba…
Live Score Following on Sheet Music Images
Matthias Dorfer, Andreas Arzt, Sebastian Böck +2
In this demo we show a novel approach to score following. Instead of relying on some symbolic representation, we are using a multi-modal convolutional neural network to match the i…
Towards End-to-End Audio-Sheet-Music Retrieval
Matthias Dorfer, Andreas Arzt, Gerhard Widmer
This paper demonstrates the feasibility of learning to retrieve short snippets of sheet music (images) when given a short query excerpt of music (audio) -- and vice versa --, witho…