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Jakob Abesser
Jakob Abesser
Fraunhofer IDMT
Verified email at idmt.fraunhofer.de
Title
Cited by
Cited by
Year
A review of deep learning based methods for acoustic scene classification
J Abeßer
Applied Sciences 10 (6), 2020, 2020
1002020
Automatic Tablature Transcription of Electric Guitar Recordings by Estimation of Score-and Instrument-Related Parameters.
C Kehling, J Abeßer, C Dittmar, G Schuller
DAFx, 219-226, 2014
722014
Music information retrieval meets music education
C Dittmar, E Cano, J Abeßer, S Grollmisch
Dagstuhl Follow-Ups 3, 2012
612012
Feature-based extraction of plucking and expression styles of the electric bass guitar
J Abeßer, H Lukashevich, G Schuller
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
502010
Inside the jazzomat: new perspectives for jazz research
M Pfleiderer, K Frieler, J Abesser, WG Zaddach, B Burkhart
Schott Music GmbH, 2017
472017
Automatic detection of audio effects in guitar and bass recordings
M Stein, J Abeßer, C Dittmar, G Schuller
Audio Engineering Society Convention 128, 2010
452010
Jazz Solo Instrument Classification with Convolutional Neural Networks, Source Separation, and Transfer Learning.
JS Gómez, J Abeßer, E Cano
ISMIR, 577-584, 2018
362018
New sonorities for jazz recordings: Separation and mixing using deep neural networks
SI Mimilakis, E Cano, J Abeßer, G Schuller
2nd AES Workshop on Intelligent Music Production 13, 2016
322016
From Multi-Labeling to Multi-Domain-Labeling: A Novel Two-Dimensional Approach to Music Genre Classification.
HM Lukashevich, J Abeßer, C Dittmar, H Grossmann
ISMIR, 459-464, 2009
312009
Sounding industry: Challenges and datasets for industrial sound analysis
S Grollmisch, J Abeßer, J Liebetrau, H Lukashevich
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
302019
Midlevel analysis of monophonic jazz solos: A new approach to the study of improvisation
K Frieler, M Pfleiderer, WG Zaddach, J Abeßer
Musicae Scientiae 20 (2), 143-162, 2016
302016
Acoustic Scene Classification by Combining Autoencoder-Based Dimensionality Reduction and Convolutional Neural Networks.
J Abeßer, SI Mimilakis, R Gräfe, HM Lukashevich, I Fraunhofer
DCASE, 7-11, 2017
282017
Automatic quality assessment of vocal and instrumental performances of ninth-grade and tenth-grade pupils
J Abeßer, J Hasselhorn, C Dittmar, A Lehmann, S Grollmisch
Proceedings of the International Symposium on Computer Music …, 2013
282013
Automatic string detection for bass guitar and electric guitar
J Abeßer
International Symposium on Computer Music Modeling and Retrieval, 333-352, 2012
272012
Automatic genre classification of latin american music using characteristic rhythmic patterns
T Völkel, J Abeßer, C Dittmar, H Großmann
Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction …, 2010
242010
Data-driven solo voice enhancement for jazz music retrieval
S Balke, C Dittmar, J Abeßer, M Müller
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
232017
Automatic classification of musical pieces into global cultural areas
A Kruspe, H Lukashevich, J Abeßer, H Großmann, C Dittmar
Audio Engineering Society Conference: 42nd International Conference …, 2011
212011
Inside the Jazzomat
M Pfleiderer, K Frieler, J Abeßer, WG Zaddach, B Burkhart
New Perspectives for Jazz Research, 2017
202017
New Sonorities for Early Jazz Recordings Using Sound Source Separation and Automatic Mixing Tools.
D Matz, E Cano, J Abeßer
ISMIR, 749-755, 2015
202015
Instrument-centered music transcription of solo bass guitar recordings
J Abeßer, G Schuller
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (9), 1741 …, 2017
192017
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