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2018
[j3]
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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)
[c56]
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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
[c55]
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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
[c54]
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Beici Liang, György Fazekas, Mark B. Sandler:
Piano Legato-Pedal Onset Detection Based on a Sympathetic Resonance Measure. EUSIPCO 2018: 2484-2488
[c53]
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  - conf/fruct/TurchetVFB18
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Luca Turchet, Fabio Viola, György Fazekas, Mathieu Barthet:
Towards a Semantic Architecture for the Internet of Musical Things. FRUCT 2018: 382-390
[c52]
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  - conf/fruct/ViolaTAF18
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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
[c51]
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Di Sheng, György Fazekas:
Feature Design Using Audio Decomposition for Intelligent Control of the Dynamic Range Compressor. ICASSP 2018: 621-625
[c50]
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  - conf/semweb/CerianiF18
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Miguel Ceriani, György Fazekas:
Audio Commons Ontology: A Data Model for an Audio Content Ecosystem. International Semantic Web Conference (2) 2018: 20-35
[c49]
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  - conf/semweb/ViolaSMCBF18
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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
2017
[c48]
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Beici Liang, György Fazekas, Mark B. Sandler:
Recognition of Piano Pedalling Techniques Using Gesture Data. Audio Mostly Conference 2017: 9:1-9:5
[c47]
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  - conf/hci/MarengoFT17
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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]
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Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional recurrent neural networks for music classification. ICASSP 2017: 2392-2396
[c45]
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Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer Learning for Music Classification and Regression Tasks. ISMIR 2017: 141-149
[c44]
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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]
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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]
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Beici Liang, György Fazekas, Andrew McPherson, Mark B. Sandler:
Piano pedaller: a measurement system for classification and visualisation of piano pedalling techniques. NIME 2017: 325-329
[c41]
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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
[i2]
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Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer learning for music classification and regression tasks. CoRR abs/1703.09179 (2017)
[i1]
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  - journals/corr/abs-1709-04396
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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]
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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. Affective Computing 7(2): 122-135 (2016)
[c40]
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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]
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  - conf/icassp/ChiliguanoF16
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Paulo Chiliguano, György Fazekas:
Hybrid music recommender using content-based and social information. ICASSP 2016: 2618-2622
[c38]
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  - conf/ismir/AllikFS16
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Alo Allik, György Fazekas, Mark B. Sandler:
An Ontology for Audio Features. ISMIR 2016: 73-79
[c37]
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  - conf/ismir/BuccoliZFSS16
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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]
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Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic Tagging Using Deep Convolutional Neural Networks. ISMIR 2016: 805-811
[c35]
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  - conf/mm/StablesMERFW16
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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]
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  - conf/mtsr/JuricF16
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Damir Juric, György Fazekas:
Knowledge Extraction from Audio Content Service Providers' API Descriptions. MTSR 2016: 55-66
[c33]
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  - conf/mtsr/Mora-McginityAF16
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Mariano Mora-Mcginity, Alo Allik, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. MTSR 2016: 291-296
[c32]
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  - conf/semco/ThalmannCFWS16
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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]
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  - conf/semweb/AllikFS16
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Alo Allik, György Fazekas, Mark B. Sandler:
Ontological Representation of Audio Features. International Semantic Web Conference (2) 2016: 3-11
[c30]
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  - conf/semweb/AllikMFS16
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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]
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  - conf/semweb/WilmeringFS16
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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]
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  - conf/um/ChoiFS16
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Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. UMAP (Extended Proceedings) 2016
2015
[c27]
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  - conf/audio/BarthetFAS15
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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]
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  - conf/icassp/TianFBS15
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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]
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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
2014
[c24]
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  - conf/ismir/TianFBS14
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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]
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  - conf/semanticaudio/BaumeFBMS14
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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]
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  - conf/semanticaudio/KolozaliFBS14
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Sefki Kolozali, György Fazekas, Mathieu Barthet, Mark B. Sandler:
A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. Semantic Audio 2014
[c21]
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  - conf/semanticaudio/LouBFS14
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Ting Lou, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Evaluation and Improvement of the Mood Conductor Interactive System. Semantic Audio 2014
[c20]
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  - conf/semweb/FontOFS14
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Frederic Font, Sergio Oramas, György Fazekas, Xavier Serra:
Extending Tagging Ontologies with Domain Specific Knowledge. International Semantic Web Conference (Posters & Demos) 2014: 209-212
2013
[j1]
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Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. IEEE Trans. Audio, Speech & Language Processing 21(10): 2207-2220 (2013)
[c19]
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  - conf/acii/FazekasBS13
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György Fazekas, Mathieu Barthet, Mark B. Sandler:
Mood Conductor: Emotion-Driven Interactive Music Performance. ACII 2013: 726
[c18]
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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]
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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]
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  - conf/esws/AllikFDS13
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Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
Facilitating Music Information Research with Shared Open Vocabularies. ESWC (Satellite Events) 2013: 178-183
[c15]
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  - conf/esws/AllikFDS13a
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Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
A Shared Vocabulary for Audio Features. ESWC (Satellite Events) 2013: 285-286
[c14]
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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]
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  - conf/icmcs/SaariBFES13
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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]
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  - conf/ismir/SaariEFBLS13
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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]
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  - conf/ismir/WilmeringFS13
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Thomas Wilmering, György Fazekas, Mark B. Sandler:
The Audio Effects Ontology. ISMIR 2013: 215-220
[c10]
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  - conf/ismir/KostaSFS13
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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]
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  - conf/ismir/BarthetMBFS13
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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]
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  - conf/wiamis/FazekasS13
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György Fazekas, Mark B. Sandler:
Describing audio production workflows on the semantic web. WIAMIS 2013: 1-4
2012
[b1]
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György Fazekas:
Semantic audio analysis utilities and applications. Queen Mary University of London, UK 2012
[c7]
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  - conf/cmmr/BarthetFS12
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Mathieu Barthet, György Fazekas, Mark B. Sandler:
Music Emotion Recognition: From Content- to Context-Based Models. CMMR 2012: 228-252
[c6]
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  - conf/ismir/TerrellFSSD12
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  - https://dblp.org/rec/conf/ismir/TerrellFSSD12
Michael Terrell, György Fazekas, Andrew Simpson, Jordan B. L. Smith, Simon Dixon:
Listening Level Changes Music Similarity. ISMIR 2012: 487-492
2011
[c5]
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Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Knowledge Representation Issues in Musical Instrument Ontology Design. ISMIR 2011: 465-470
[c4]
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György Fazekas, Mark B. Sandler:
The Studio Ontology Framework. ISMIR 2011: 471-476
[c3]
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György Fazekas, Thomas Wilmering, Mark B. Sandler:
A Knowledge Representation Framework for Context-Dependent Audio Processing. Semantic Audio 2011
2010
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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

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2009
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Dan Tidhar, György Fazekas, Sefki Kolozali, Mark B. Sandler:
Publishing Music Similarity Features on the Semantic Web. ISMIR 2009: 447-452

Coauthor Index

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