224 citations · 650 across the 25 of their papers we have counts for
9 papers · 1 filter
Interference Reduction in Music Recordings Combining Kernel Additive Modelling and Non-Negative Matrix Factorization
Delia Fano Yela, Sebastian Ewert, Derry FitzGerald +1
In live and studio recordings unexpected sound events often lead to interferences in the signal. For non-stationary interferences, sound source separation techniques can be used to…
Structured Dropout for Weak Label and Multi-Instance Learning and Its Application to Score-Informed Source Separation
Sebastian Ewert, Mark B. Sandler
Many success stories involving deep neural networks are instances of supervised learning, where available labels power gradient-based learning methods. Creating such labels, howeve…
Convolutional Recurrent Neural Networks for Music Classification
Keunwoo Choi, George Fazekas, Mark Sandler +1
We introduce a convolutional recurrent neural network (CRNN) for music tagging. CRNNs take advantage of convolutional neural networks (CNNs) for local feature extraction and recurr…
Towards Music Captioning: Generating Music Playlist Descriptions
Keunwoo Choi, George Fazekas, Brian McFee +2
Descriptions are often provided along with recommendations to help users' discovery. Recommending automatically generated music playlists (e.g. personalised playlists) introduces t…
Piano Transcription in the Studio Using an Extensible Alternating Directions Framework
Sebastian Ewert, Mark Sandler
Given a musical audio recording, the goal of automatic music transcription is to determine a score-like representation of the piece underlying the recording. Despite significant in…
Explaining Deep Convolutional Neural Networks on Music Classification
Keunwoo Choi, George Fazekas, Mark Sandler
Deep convolutional neural networks (CNNs) have been actively adopted in the field of music information retrieval, e.g. genre classification, mood detection, and chord recognition.…