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ORCIDMark B. Sandler
Mark Sandler 0001
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- affiliation: Queen Mary University of London, UK
Other persons with the same name
- Mark Sandler 0002
![[0000-0003-0352-6051]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0352-6051")
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2020 – today
- 2022
[c149]Yudong Zhao, György Fazekas, Mark Sandler:
Transfer Learning for Violinist Identification. EUSIPCO 2022: 239-243- [c148]Jeff Miller, Ken O'Hanlon, Mark B. Sandler:
Improving Balance in Automatic Chord Recognition with Random Forests. EUSIPCO 2022: 244-248 - [c147]Yudong Zhao, György Fazekas, Mark B. Sandler:
Violinist Identification Using Note-Level Timbre Feature Distributions. ICASSP 2022: 601-605 - [i30]Alejandro Delgado, Emir Demirel, Vinod Subramanian, Charalampos Saitis, Mark B. Sandler:
Deep Embeddings for Robust User-Based Amateur Vocal Percussion Classification. CoRR abs/2204.04646 (2022) - [i29]Alejandro Delgado, Charalampos Saitis, Emmanouil Benetos, Mark B. Sandler:
Deep Conditional Representation Learning for Drum Sample Retrieval by Vocalisation. CoRR abs/2204.04651 (2022) - [i28]Vinod Subramanian, Siddharth Gururani, Emmanouil Benetos, Mark B. Sandler:
Anomalous behaviour in loss-gradient based interpretability methods. CoRR abs/2207.07769 (2022) - [i27]Franco Caspe, Andrew McPherson, Mark Sandler:
DDX7: Differentiable FM Synthesis of Musical Instrument Sounds. CoRR abs/2208.06169 (2022) - [i26]Rodrigo Diaz, Ben Hayes, Charalampos Saitis, György Fazekas, Mark Sandler:
Rigid-Body Sound Synthesis with Differentiable Modal Resonators. CoRR abs/2210.15306 (2022) - 2021
- [j51]Ken O'Hanlon, Mark B. Sandler:
FifthNet: Structured Compact Neural Networks for Automatic Chord Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2671-2682 (2021) - [c146]Jeff Miller, Vincenzo Nicosia, Mark Sandler:
Discovering Common Practice: Using Graph Theory to Compare Harmonic Sequences in Musical Audio Collections. DLfM 2021: 93-97 - [c145]Yudong Zhao, Changhong Wang, György Fazekas, Emmanouil Benetos, Mark B. Sandler:
Violinist identification based on vibrato features. EUSIPCO 2021: 381-385 - [c144]Saurjya Sarkar, Emmanouil Benetos, Mark B. Sandler:
Vocal Harmony Separation Using Time-Domain Neural Networks. Interspeech 2021: 3515-3519 - [i25]Beici Liang, György Fazekas, Mark B. Sandler:
Transfer Learning for Piano Sustain-Pedal Detection. CoRR abs/2103.13219 (2021) - [i24]Alejandro Delgado, SKoT McDonald, Ning Xu, Charalampos Saitis, Mark B. Sandler:
Learning Models for Query by Vocal Percussion: A Comparative Study. CoRR abs/2110.09223 (2021) - 2020
- [j50]Cornelia Metzig, Matthew Gould, Roshan Noronha, Roshani Abbey, Mark Sandler, Caroline Colijn:
Classification of origin with feature selection and network construction for folk tunes. Pattern Recognit. Lett. 133: 356-364 (2020) - [j49]Panos Kudumakis, Thomas Wilmering, Mark B. Sandler, Víctor Rodríguez-Doncel, Laurent Boch, Jaime Delgado:
The Challenge: From MPEG Intellectual Property Rights Ontologies to Smart Contracts and Blockchains [Standards in a Nutshell]. IEEE Signal Process. Mag. 37(2): 89-95 (2020) - [j48]Florian Thalmann, Geraint A. Wiggins, Mark B. Sandler:
Representing Modifiable and Reusable Musical Content on the Web With Constrained Multi-Hierarchical Structures. IEEE Trans. Multim. 22(10): 2645-2658 (2020) - [c143]Vinod Subramanian, Arjun Pankajakshan, Emmanouil Benetos, Ning Xu, SKoT McDonald, Mark B. Sandler:
A Study on the Transferability of Adversarial Attacks in Sound Event Classification. ICASSP 2020: 301-305 - [c142]Ken O'Hanlon, Mark B. Sandler:
The Fifthnet Chroma Extractor. ICASSP 2020: 3752-3756 - [c141]Fred Bruford, Olivier Lartillot, SKoT McDonald, Mark B. Sandler:
Multidimensional similarity modelling of complex drum loops using the GrooveToolbox. ISMIR 2020: 263-270 - [c140]Florian Thalmann, Kazuyoshi Yoshii, Thomas Wilmering, Geraint A. Wiggins, Mark B. Sandler:
A Method for Analysis of Shared Structure in Large Music Collections using Techniques from Genetic Sequencing and Graph Theory. ISMIR 2020: 343-350 - [i23]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)
2010 – 2019
- 2019
- [c139]Alejandro Delgado, SKoT McDonald, Ning Xu, Mark B. Sandler:
A New Dataset for Amateur Vocal Percussion Analysis. Audio Mostly Conference 2019: 17-23 - [c138]Fred Bruford, Mathieu Barthet, SKoT McDonald, Mark B. Sandler:
Modelling Musical Similarity for Drum Patterns: A Perceptual Evaluation. Audio Mostly Conference 2019: 131-138 - [c137]Dalia Senvaityte, Johan Pauwels, Mark B. Sandler:
Guitar String Separation Using Non-Negative Matrix Factorization and Factor Deconvolution. Audio Mostly Conference 2019: 239-243 - [c136]Vinod Subramanian, Emmanouil Benetos, Mark B. Sandler:
Robustness of Adversarial Attacks in Sound Event Classification. DCASE 2019: 239-243 - [c135]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Spectral Visibility Graphs: Application to Similarity of Harmonic Signals. EUSIPCO 2019: 1-5 - [c134]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Sustain-pedal Detection Using Convolutional Neural Networks. ICASSP 2019: 241-245 - [c133]Ken O'Hanlon, Mark B. Sandler:
Comparing CQT and Reassignment Based Chroma Features for Template-based Automatic Chord Recognition. ICASSP 2019: 860-864 - [c132]Beici Liang, György Fazekas, Mark B. Sandler:
Transfer Learning for Piano Sustain-Pedal Detection. IJCNN 2019: 1-6 - [c131]Johan Pauwels, Ken O'Hanlon, Emilia Gómez, Mark B. Sandler:
20 Years of Automatic Chord Recognition from Audio. ISMIR 2019: 54-63 - [c130]Fred Bruford, Mathieu Barthet, SKoT McDonald, Mark B. Sandler:
Groove Explorer: An Intelligent Visual Interface for Drum Loop Library Navigation. IUI Workshops 2019 - [c129]Johan Pauwels, Mark B. Sandler:
A Web-Based System For Suggesting New Practice Material To Music Learners Based On Chord Content. IUI Workshops 2019 - [c128]Panos Kudumakis, Thomas Wilmering, Mark B. Sandler, Jeremy D. Foss:
MPEG Intellectual Property Rights Ontologies for Media Trading and Personalization. DataTV@TVX 2019 - [i22]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Visibility graphs for robust harmonic similarity measures between audio spectra. CoRR abs/1903.01976 (2019) - [i21]Delia Fano Yela, Florian Thalmann, Vincenzo Nicosia, Dan Stowell, Mark B. Sandler:
Efficient On-line Computation of Visibility Graphs. CoRR abs/1905.03204 (2019) - [i20]Vinod Subramanian, Emmanouil Benetos, Ning Xu, SKoT McDonald, Mark B. Sandler:
Adversarial Attacks in Sound Event Classification. CoRR abs/1907.02477 (2019) - 2018
- [j47]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging. IEEE Trans. Emerg. Top. Comput. Intell. 2(2): 139-149 (2018) - [c127]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 - [c126]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Legato-Pedal Onset Detection Based on a Sympathetic Resonance Measure. EUSIPCO 2018: 2484-2488 - [c125]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation. LVA/ICA 2018: 280-289 - [c124]Adib Mehrabi, Keunwoo Choi, Simon Dixon, Mark B. Sandler:
Similarity Measures for Vocal-Based Drum Sample Retrieval Using Deep Convolutional Auto-Encoders. ICASSP 2018: 356-360 - [c123]Ken O'Hanlon, Mark B. Sandler:
Improved Detection of Semi-Percussive Onsets in Audio Using Temporal Reassignment. ICASSP 2018: 611-615 - [c122]Delia Fano Yela, Sebastian Ewert, Ken O'Hanlon, Mark B. Sandler:
Shift-Invariant Kernel Additive Modelling for Audio Source Separation. ICASSP 2018: 616-620 - [c121]Florian Thalmann, Thomas Wilmering, Mark B. Sandler:
Cultural Heritage Documentation and Exploration of Live Music Events with Linked Data. SAAM@ISWC 2018: 1-5 - [c120]Thomas Wilmering, Florian Thalmann, Mark B. Sandler:
Exploration of Grateful Dead Concerts and Memorabilia on the Semantic Web. ISWC (P&D/Industry/BlueSky) 2018 - [c119]Alo Allik, Florian Thalmann, Mark B. Sandler:
MusicLynx: Exploring Music Through Artist Similarity Graphs. WWW (Companion Volume) 2018: 167-170 - [i19]Adib Mehrabi, Keunwoo Choi, Simon Dixon, Mark B. Sandler:
Similarity measures for vocal-based drum sample retrieval using deep convolutional auto-encoders. CoRR abs/1802.05178 (2018) - [i18]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation. CoRR abs/1804.02325 (2018) - 2017
- [j46]Mi Tian, Mark B. Sandler:
Towards Music Structural Segmentation across Genres: Features, Structural Hypotheses, and Annotation Principles. ACM Trans. Intell. Syst. Technol. 8(2): 23:1-23:19 (2017) - [c118]Beici Liang, György Fazekas, Mark B. Sandler:
Recognition of Piano Pedalling Techniques Using Gesture Data. Audio Mostly Conference 2017: 9:1-9:5 - [c117]Angela McArthur, Mark Sandler, Rebecca Stewart:
Distance in audio for VR: constraints and opportunities. Audio Mostly Conference 2017: 28:1-28:7 - [c116]Ben White, Adib Mehrabi, Mark B. Sandler:
An Archival Echo: Recalling the public domain through real-time query by vocalisation. Audio Mostly Conference 2017: 42:1-42:4 - [c115]Elio Quinton, Ken O'Hanlon, Simon Dixon, Mark B. Sandler:
Tracking metrical structure changes with sparse-NMF. ICASSP 2017: 41-45 - [c114]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
Interference reduction in music recordings combining Kernel Additive Modelling and Non-Negative Matrix Factorization. ICASSP 2017: 51-55 - [c113]Ken O'Hanlon, Sebastian Ewert, Johan Pauwels, Mark B. Sandler:
Improved template based chord recognition using the CRP feature. ICASSP 2017: 306-310 - [c112]Sebastian Ewert, Mark B. Sandler:
Structured dropout for weak label and multi-instance learning and its application to score-informed source separation. ICASSP 2017: 2277-2281 - [c111]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional recurrent neural networks for music classification. ICASSP 2017: 2392-2396 - [c110]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer Learning for Music Classification and Regression Tasks. ISMIR 2017: 141-149 - [c109]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 - [c108]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 - [c107]Delia Fano Yela, Sebastian Ewert, Derry Fitzgerald, Mark B. Sandler:
On the Importance of Temporal Context in Proximity Kernels: A Vocal Separation Case Study. Semantic Audio 2017 - [c106]Sebastian Ewert, Mark B. Sandler:
An augmented lagrangian method for piano transcription using equal loudness thresholding and lstm-based decoding. WASPAA 2017: 146-150 - [i17]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
On the Importance of Temporal Context in Proximity Kernels: A Vocal Separation Case Study. CoRR abs/1702.02130 (2017) - [i16]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer learning for music classification and regression tasks. CoRR abs/1703.09179 (2017) - [i15]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) - [i14]Sebastian Ewert, Mark B. Sandler:
An Augmented Lagrangian Method for Piano Transcription using Equal Loudness Thresholding and LSTM-based Decoding. CoRR abs/1707.00160 (2017) - [i13]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) - [i12]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Tutorial on Deep Learning for Music Information Retrieval. CoRR abs/1709.04396 (2017) - [i11]Delia Fano Yela, Sebastian Ewert, Ken O'Hanlon, Mark B. Sandler:
Shift-Invariant Kernel Additive Modelling for Audio Source Separation. CoRR abs/1711.00351 (2017) - 2016
- [j45]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) - [j44]Sebastian Ewert, Mark B. Sandler:
Piano Transcription in the Studio Using an Extensible Alternating Directions Framework. IEEE ACM Trans. Audio Speech Lang. Process. 24(11): 1983-1997 (2016) - [c105]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 - [c104]Ken O'Hanlon, Mark B. Sandler:
Compositional chroma estimation using powered Euclidean distance. EUSIPCO 2016: 1237-1241 - [c103]Francisco J. Rodríguez-Serrano, Sebastian Ewert, Pedro Vera-Candeas, Mark B. Sandler:
A score-informed shift-invariant extension of complex matrix factorization for improving the separation of overlapped partials in music recordings. ICASSP 2016: 61-65 - [c102]Elio Quinton, Mark B. Sandler, Simon Dixon:
Estimation of the reliability of multiple rhythm features extraction from a single descriptor. ICASSP 2016: 256-260 - [c101]Ken O'Hanlon, Mark B. Sandler:
An iterative hard thresholding approach to ℓ0 sparse Hellinger NMF. ICASSP 2016: 4737-4741 - [c100]Sebastian Ewert, Siying Wang, Meinard Müller, Mark B. Sandler:
Score-Informed Identification of Missing and Extra Notes in Piano Recordings. ISMIR 2016: 30-36 - [c99]Alo Allik, György Fazekas, Mark B. Sandler:
An Ontology for Audio Features. ISMIR 2016: 73-79 - [c98]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 - [c97]Mi Tian, Mark B. Sandler:
Music Structural Segmentation Across Genres with Gammatone Features. ISMIR 2016: 561-567 - [c96]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic Tagging Using Deep Convolutional Neural Networks. ISMIR 2016: 805-811 - [c95]Mariano Mora-Mcginity, Alo Allik, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. MTSR 2016: 291-296 - [c94]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 - [c93]Alo Allik, György Fazekas, Mark B. Sandler:
Ontological Representation of Audio Features. ISWC (2) 2016: 3-11 - [c92]Alo Allik, Mariano Mora-Mcginity, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. ISWC (Posters & Demos) 2016 - [c91]Thomas Wilmering, György Fazekas, Mark B. Sandler:
AUFX-O: Novel Methods for the Representation of Audio Processing Workflows. ISWC (2) 2016: 229-237 - [c90]Thomas Wilmering, Mark B. Sandler:
Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology. ISWC (Posters & Demos) 2016 - [c89]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. UMAP (Extended Proceedings) 2016 - [i10]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Text-based LSTM networks for Automatic Music Composition. CoRR abs/1604.05358 (2016) - [i9]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic tagging using deep convolutional neural networks. CoRR abs/1606.00298 (2016) - [i8]Sebastian Ewert, Mark B. Sandler:
Piano Transcription in the Studio Using an Extensible Alternating Directions Framework. CoRR abs/1606.00785 (2016) - [i7]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. CoRR abs/1606.02096 (2016) - [i6]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Explaining Deep Convolutional Neural Networks on Music Classification. CoRR abs/1607.02444 (2016) - [i5]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Music Captioning: Generating Music Playlist Descriptions. CoRR abs/1608.04868 (2016) - [i4]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional Recurrent Neural Networks for Music Classification. CoRR abs/1609.04243 (2016) - [i3]Sebastian Ewert, Mark B. Sandler:
Structured Dropout for Weak Label and Multi-Instance Learning and Its Application to Score-Informed Source Separation. CoRR abs/1609.04557 (2016) - [i2]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
Interference Reduction in Music Recordings Combining Kernel Additive Modelling and Non-Negative Matrix Factorization. CoRR abs/1609.06210 (2016) - 2015
- [c88]Mathieu Barthet, György Fazekas, Alo Allik, Mark B. Sandler:
Moodplay: an interactive mood-based musical experience. Audio Mostly Conference 2015: 3:1-3:8 - [c87]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 - [c86]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
A dynamic programming variant of non-negative matrix deconvolution for the transcription of struck string instruments. ICASSP 2015: 569-573 - [c85]Ken O'Hanlon, Mark B. Sandler, Mark D. Plumbley:
Non-negative matrix factorisation incorporating greedy hellinger sparse coding applied to polyphonic music transcription. ICASSP 2015: 2214-2218 - [i1]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Understanding Music Playlists. CoRR abs/1511.07004 (2015) - 2014
- [j43]Panos Kudumakis, Mark B. Sandler, Angelos-Christos G. Anadiotis, Iakovos S. Venieris, Angelo Difino, Xin Wang, Giuseppe Tropea, Michael Grafl, Víctor Rodríguez-Doncel, Silvia Llorente, Jaime Delgado:
MPEG-M: A digital media ecosystem for interoperable applications. Signal Process. Image Commun. 29(1): 150-166 (2014) - [c84]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
Accounting for phase cancellations in non-negative matrix factorization using weighted distances. ICASSP 2014: 649-653 - [c83]Mi Tian, Ajay Srinivasamurthy, Mark B. Sandler, Xavier Serra:
A study of instrument-wise onset detection in Beijing Opera percussion ensembles. ICASSP 2014: 2159-2163 - [c82]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 - [c81]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 - [c80]Carl Bussey, Michael Terrell, Raihan Rahman, Mark B. Sandler:
Metadata Features that Affect Artificial Reverberator Intensity. Semantic Audio 2014 - [c79]Rubén Jesús García, Costantino Taglialatela, Panos Kudumakis, Isabel Barbancho, Lorenzo J. Tardón, Mark B. Sandler:
Interactive Music Applications by MPEG-A Support in Sonic Visualizer. Semantic Audio 2014 - [c78]Steven Hargreaves, Geraint A. Wiggins, Mark B. Sandler:
A Semantic Web Approach to Pattern Discovery in Data and Music. Semantic Audio 2014 - [c77]Sefki Kolozali, György Fazekas, Mathieu Barthet, Mark B. Sandler:
A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. Semantic Audio 2014 - [c76]Ting Lou, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Evaluation and Improvement of the Mood Conductor Interactive System. Semantic Audio 2014 - 2013
- [j42]Xue Wen, Mark Sandler:
Fast Additive Sinusoidal Synthesis With a Subband Sinusoidal Method. IEEE Signal Process. Lett. 20(5): 467-470 (2013) - [j41]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) - [c75]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Mood Conductor: Emotion-Driven Interactive Music Performance. ACII 2013: 726 - [c74]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Novel Methods in Facilitating Audience and Performer Interaction Using the Mood Conductor Framework. CMMR 2013: 122-147 - [c73]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