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Semantic ScholarGyörgy Fazekas
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2020 – today
- 2020
[j4]Luca Turchet
, Francesco Antoniazzi, Fabio Viola, Fausto Giunchiglia, György Fazekas:
The Internet of Musical Things Ontology. J. Web Semant. 60: 100548 (2020)- [i14]Johan Pauwels, György Fazekas, Mark B. Sandler:
A Critical Look at the Applicability of Markov Logic Networks for Music Signal Analysis. CoRR abs/2001.06086 (2020) - [i13]Elona Shatri, György Fazekas:
Optical Music Recognition: State of the Art and Major Challenges. CoRR abs/2006.07885 (2020)
2010 – 2019
- 2019
- [c62]Gary Bromham, David Moffat, Mathieu Barthet, Anne Danielsen, György Fazekas:
The Impact of Audio Effects Processing on the Perception of Brightness and Warmth. Audio Mostly Conference 2019: 183-190 - [c61]Andrew Thompson, György Fazekas:
A Model-View-Update Framework for Interactive Web Audio Applications. Audio Mostly Conference 2019: 219-222 - [c60]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Sustain-pedal Detection Using Convolutional Neural Networks. ICASSP 2019: 241-245 - [c59]Beici Liang, György Fazekas, Mark B. Sandler:
Transfer Learning for Piano Sustain-Pedal Detection. IJCNN 2019: 1-6 - [c58]Di Sheng, György Fazekas:
A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor. IJCNN 2019: 1-8 - [i12]Di Sheng, György Fazekas:
A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor. CoRR abs/1905.01022 (2019) - 2018
- [j3]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging. IEEE Trans. Emerging Topics in Comput. Intellig. 2(2): 139-149 (2018) - [c57]Anna Xambó, Johan Pauwels, Gerard Roma, Mathieu Barthet, György Fazekas:
Jam with Jamendo: Querying a Large Music Collection by Chords from a Learner's Perspective. Audio Mostly Conference 2018: 30:1-30:7 - [c56]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. EUSIPCO 2018: 1870-1874 - [c55]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Legato-Pedal Onset Detection Based on a Sympathetic Resonance Measure. EUSIPCO 2018: 2484-2488 - [c54]Luca Turchet, Fabio Viola, György Fazekas, Mathieu Barthet:
Towards a Semantic Architecture for the Internet of Musical Things. FRUCT 2018: 382-390 - [c53]Fabio Viola, Luca Turchet, Francesco Antoniazzi, György Fazekas:
C Minor: a Semantic Publish/Subscribe Broker for the Internet of Musical Things. FRUCT 2018: 405-415 - [c52]Di Sheng, György Fazekas:
Feature Design Using Audio Decomposition for Intelligent Control of the Dynamic Range Compressor. ICASSP 2018: 621-625 - [c51]Anna Xambó, Gerard Roma, Alexander Lerch, Mathieu Barthet, György Fazekas:
Live Repurposing of Sounds: MIR Explorations with Personal and Crowdsourced Databases. NIME 2018: 364-369 - [c50]Miguel Ceriani, György Fazekas:
Audio Commons Ontology: A Data Model for an Audio Content Ecosystem. International Semantic Web Conference (2) 2018: 20-35 - [c49]Fabio Viola, Ariane Stolfi, Alessia Milo, Miguel Ceriani, Mathieu Barthet, György Fazekas:
Playsound.space: enhancing a live music performance tool with semantic recommendations. SAAM@ISWC 2018: 46-53 - [e3]Sean Bechhofer, György Fazekas, Kevin R. Page:
Proceedings of the 1st International Workshop on Semantic Applications for Audio and Music, SAAM@ISWC 2018, Monterey, CA, USA, October 9, 2018. ACM 2018, ISBN 978-1-4503-6495-9 [contents] - 2017
- [c48]Beici Liang, György Fazekas, Mark B. Sandler:
Recognition of Piano Pedalling Techniques Using Gesture Data. Audio Mostly Conference 2017: 9:1-9:5 - [c47]Lucia Marengo, György Fazekas, Anastasios Tombros:
The Interaction of Casual Users with Digital Collections of Visual Art. An Exploratory Study of the WikiArt Website. HCI (30) 2017: 583-590 - [c46]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional recurrent neural networks for music classification. ICASSP 2017: 2392-2396 - [c45]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer Learning for Music Classification and Regression Tasks. ISMIR 2017: 141-149 - [c44]Johan Pauwels, Ken O'Hanlon, György Fazekas, Mark B. Sandler:
Confidence Measures and Their Applications in Music Labelling Systems Based on Hidden Markov Models. ISMIR 2017: 279-285 - [c43]Kevin R. Page, Sean Bechhofer, György Fazekas, David M. Weigl, Thomas Wilmering:
Realising a Layered Digital Library: Exploration and Analysis of the Live Music Archive through Linked Data. JCDL 2017: 89-98 - [c42]Beici Liang, György Fazekas, Andrew P. McPherson, Mark B. Sandler:
Piano pedaller: a measurement system for classification and visualisation of piano pedalling techniques. NIME 2017: 325-329 - [c41]Sean Bechhofer, Kevin R. Page, David M. Weigl, György Fazekas, Thomas Wilmering:
Linked Data Publication of Live Music Archives and Analyses. International Semantic Web Conference (2) 2017: 29-37 - [e2]György Fazekas, Mathieu Barthet, Tony Stockman:
Proceedings of the 12th International Audio Mostly Conference on Augmented and Participatory Sound and Music Experiences, London, United Kingdom, August 23 - 26, 2017. ACM 2017, ISBN 978-1-4503-5373-1 [contents] - [i11]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer learning for music classification and regression tasks. CoRR abs/1703.09179 (2017) - [i10]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
On the Robustness of Deep Convolutional Neural Networks for Music Classification. CoRR abs/1706.02361 (2017) - [i9]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. CoRR abs/1709.01922 (2017) - [i8]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Tutorial on Deep Learning for Music Information Retrieval. CoRR abs/1709.04396 (2017) - 2016
- [j2]Pasi Saari, György Fazekas, Tuomas Eerola, Mathieu Barthet, Olivier Lartillot, Mark B. Sandler:
Genre-Adaptive Semantic Computing and Audio-Based Modelling for Music Mood Annotation. IEEE Trans. Affect. Comput. 7(2): 122-135 (2016) - [c40]Florian Thalmann, György Fazekas, Geraint A. Wiggins, Mark B. Sandler:
Creating, Visualizing, and Analyzing Dynamic Music Objects in the Browser with the Dymo Designer. Audio Mostly Conference 2016: 39-46 - [c39]Paulo Chiliguano, György Fazekas:
Hybrid music recommender using content-based and social information. ICASSP 2016: 2618-2622 - [c38]Alo Allik, György Fazekas, Mark B. Sandler:
An Ontology for Audio Features. ISMIR 2016: 73-79 - [c37]Michele Buccoli, Massimiliano Zanoni, György Fazekas, Augusto Sarti, Mark B. Sandler:
A Higher-Dimensional Expansion of Affective Norms for English Terms for Music Tagging. ISMIR 2016: 316-322 - [c36]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic Tagging Using Deep Convolutional Neural Networks. ISMIR 2016: 805-811 - [c35]Ryan Stables, Brecht De Man, Sean Enderby, Joshua D. Reiss, György Fazekas, Thomas Wilmering:
Semantic Description of Timbral Transformations in Music Production. ACM Multimedia 2016: 337-341 - [c34]Damir Juric, György Fazekas:
Knowledge Extraction from Audio Content Service Providers' API Descriptions. MTSR 2016: 55-66 - [c33]Mariano Mora-Mcginity, Alo Allik, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. MTSR 2016: 291-296 - [c32]Florian Thalmann, Alfonso Pérez Carrillo, György Fazekas, Geraint A. Wiggins, Mark B. Sandler:
The Mobile Audio Ontology: Experiencing Dynamic Music Objects on Mobile Devices. ICSC 2016: 47-54 - [c31]Alo Allik, György Fazekas, Mark B. Sandler:
Ontological Representation of Audio Features. International Semantic Web Conference (2) 2016: 3-11 - [c30]Alo Allik, Mariano Mora-Mcginity, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. International Semantic Web Conference (Posters & Demos) 2016 - [c29]Thomas Wilmering, György Fazekas, Mark B. Sandler:
AUFX-O: Novel Methods for the Representation of Audio Processing Workflows. International Semantic Web Conference (2) 2016: 229-237 - [c28]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. UMAP (Extended Proceedings) 2016 - [i7]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Text-based LSTM networks for Automatic Music Composition. CoRR abs/1604.05358 (2016) - [i6]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic tagging using deep convolutional neural networks. CoRR abs/1606.00298 (2016) - [i5]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. CoRR abs/1606.02096 (2016) - [i4]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Explaining Deep Convolutional Neural Networks on Music Classification. CoRR abs/1607.02444 (2016) - [i3]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Music Captioning: Generating Music Playlist Descriptions. CoRR abs/1608.04868 (2016) - [i2]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional Recurrent Neural Networks for Music Classification. CoRR abs/1609.04243 (2016) - 2015
- [c27]Mathieu Barthet, György Fazekas, Alo Allik, Mark B. Sandler:
Moodplay: an interactive mood-based musical experience. Audio Mostly Conference 2015: 3:1-3:8 - [c26]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
On the use of the tempogram to describe audio content and its application to Music structural segmentation. ICASSP 2015: 419-423 - [c25]Thomas Wilmering, Kevin R. Page, György Fazekas, Simon Dixon, Sean Bechhofer:
Automating Annotation of Media with Linked Data Workflows. WWW (Companion Volume) 2015: 737-738 - [i1]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Understanding Music Playlists. CoRR abs/1511.07004 (2015) - 2014
- [c24]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
Design And Evaluation of Onset Detectors using Different Fusion Policies. ISMIR 2014: 631-636 - [c23]Chris Baume, György Fazekas, Mathieu Barthet, David Marston, Mark B. Sandler:
Selection of Audio Features for Music Emotion Recognition Using Production Music. Semantic Audio 2014 - [c22]Sefki Kolozali, György Fazekas, Mathieu Barthet, Mark B. Sandler:
A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. Semantic Audio 2014 - [c21]Ting Lou, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Evaluation and Improvement of the Mood Conductor Interactive System. Semantic Audio 2014 - [c20]Frederic Font, Sergio Oramas, György Fazekas, Xavier Serra:
Extending Tagging Ontologies with Domain Specific Knowledge. International Semantic Web Conference (Posters & Demos) 2014: 209-212 - [e1]Christian Dittmar, György Fazekas, Sebastian Ewert:
AES International Conference on Semantic Audio 2014, London, UK, January 27-29, 2014. Audio Engineering Society 2014, ISBN 978-0-937803-96-7 [contents] - 2013
- [j1]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. IEEE Trans. Speech Audio Process. 21(10): 2207-2220 (2013) - [c19]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Mood Conductor: Emotion-Driven Interactive Music Performance. ACII 2013: 726 - [c18]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Novel Methods in Facilitating Audience and Performer Interaction Using the Mood Conductor Framework. CMMR 2013: 122-147 - [c17]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
Towards the Representation of Chinese Traditional Music: A State of the Art Review of Music Metadata Standards. Dublin Core Conference 2013: 71-81 - [c16]Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
Facilitating Music Information Research with Shared Open Vocabularies. ESWC (Satellite Events) 2013: 178-183 - [c15]Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
A Shared Vocabulary for Audio Features. ESWC (Satellite Events) 2013: 285-286 - [c14]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Demo paper: The BBC Desktop Jukebox music recommendation system: A large scale trial with professional users. ICME Workshops 2013: 1-2 - [c13]Pasi Saari, Mathieu Barthet, György Fazekas, Tuomas Eerola, Mark B. Sandler:
Semantic models of musical mood: Comparison between crowd-sourced and curated editorial tags. ICME Workshops 2013: 1-6 - [c12]Pasi Saari, Tuomas Eerola, György Fazekas, Mathieu Barthet, Olivier Lartillot, Mark B. Sandler:
The Role of Audio and Tags in Music Mood Prediction: A Study Using Semantic Layer Projection. ISMIR 2013: 201-206 - [c11]Thomas Wilmering, György Fazekas, Mark B. Sandler:
The Audio Effects Ontology. ISMIR 2013: 215-220 - [c10]Katerina Kosta, Yading Song, György Fazekas, Mark B. Sandler:
A Study of Cultural Dependence of Perceived Mood in Greek Music. ISMIR 2013: 317-322 - [c9]Mathieu Barthet, David Marston, Chris Baume, György Fazekas, Mark B. Sandler:
Design and Evaluation of Semantic Mood Models for Music Recommendation using Editorial Tags. ISMIR 2013: 421-426 - [c8]György Fazekas, Mark B. Sandler:
Describing audio production workflows on the semantic web. WIAMIS 2013: 1-4 - 2012
- [b1]György Fazekas:
Semantic audio analysis utilities and applications. Queen Mary University of London, UK, 2012 - [c7]Mathieu Barthet, György Fazekas, Mark B. Sandler:
Music Emotion Recognition: From Content- to Context-Based Models. CMMR 2012: 228-252 - [c6]Michael Terrell, György Fazekas, Andrew Simpson, Jordan B. L. Smith, Simon Dixon:
Listening Level Changes Music Similarity. ISMIR 2012: 487-492 - 2011
- [c5]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Knowledge Representation Issues in Musical Instrument Ontology Design. ISMIR 2011: 465-470 - [c4]György Fazekas, Mark B. Sandler:
The Studio Ontology Framework. ISMIR 2011: 471-476 - [c3]György Fazekas, Thomas Wilmering, Mark B. Sandler:
A Knowledge Representation Framework for Context-Dependent Audio Processing. Semantic Audio 2011 - 2010
- [c2]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Towards the Automatic Generation of a Semantic Web Ontology for Musical Instruments. SAMT 2010: 186-187
2000 – 2009
- 2009
- [c1]Dan Tidhar, György Fazekas, Sefki Kolozali, Mark B. Sandler:
Publishing Music Similarity Features on the Semantic Web. ISMIR 2009: 447-452
Coauthor Index
[i14] [c60] [c59] [j3] [c56] [c55] [c48] [c46] [c45] [c44] [c42] [i11] [i10] [i9] [i8] [j2] [c40] [c38] [c37] [c36] [c33] [c32] [c31] [c30] [c29] [c28] [i7] [i6] [i5] [i4] [i3] [i2] [c27] [c26] [i1] [c24] [c23] [c22] [c21] [j1] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c5] [c4] [c3] [c2] [c1]
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