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School of Electronic Engineering and Computer Science

Photo of Simon Dixon Prof. Simon Dixon

Contact Details

Position: Professor;
Director of the UKRI Centre for Doctoral Training in Artificial Intelligence and Music;
Deputy Director of the Centre for Digital Music
Tel: Internal: [13] 7681
International: +44 20 7882 7681
Email: s.e.dixon@qmul.ac.uk
Office: ENG 406 (access from ENG403 via 4th floor of Graduate Centre)
Office Hours: Tue 3pm during semester.
Please mail me in advance to confirm availability or to request an appointment at other times.
Research Group: Centre for Digital Music
Google Scholar: http://scholar.google.co.uk/citations?user=9GvyqXEAAAAJ
ORCID ID: 0000-0002-6098-481X

News & Events

Press

Articles about some of the research projects I have worked on appeared in:

Research

My research interests are in the fields of music informatics (music information retrieval), artificial intelligence, computer music, music signal processing, digital audio and music cognition. In recent years I have mainly worked on high-level music signal analysis, computational modelling of musical knowledge, and the study of musical performance, rhythm, harmony and intonation. For example, I have worked on note and chord transcription, beat tracking, multimodal music alignment, and singing intonation, using signal processing approaches, probabilistic models, and deep learning.

Projects

Publications

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Link to my page on Google Scholar.

Mary Pilataki, Matthias Mauch and Simon Dixon (2024),
Pitch-Aware Generative Pretraining Improves Multi-pitch Estimation with Scarce Data.
ACM Multimedia Asia, to appear.

Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi, Wei-Hsiang Liao, Keisuke Toyama, Toshimitsu Uesaka, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Simon Dixon, Yuki Mitsufuji (2024),
Disentangling Multi-instrument Music Audio for Source-Level Pitch and Timbre Manipulation.
Audio Imagination: NeurIPS 2024 Workshop, to appear.

Xavier Riley, Zixun Guo, Andrew Edwards and Simon Dixon (2024),
GAPS: A Large and Diverse Classical Guitar Dataset and Benchmark Transcription Model.
International Society for Music Information Retrieval Conference, to appear.

Huan Zhang, Jinhua Liang and Simon Dixon (2024),
From Audio Encoders to Piano Judges: Benchmarking Performance Understanding for Solo Piano.
International Society for Music Information Retrieval Conference, to appear.

Andrew Edwards, Xavier Riley, Pedro Sarmento and Simon Dixon (2024),
MIDI-to-Tab: Guitar Tablature Inference via Masked Language Modeling.
International Society for Music Information Retrieval Conference, to appear.

S. Chang, E. Benetos, H. Kirchhoff and S. Dixon (2024),
YourMT3+: Multi-instrument Music Transcription with Enhanced Transformer Architectures and Cross-Dataset Stem Augmentation.
IEEE International Workshop on Machine Learning for Signal Processing (MLSP), to appear. arXiv preprint 2407.04822.

Huan Zhang, Shreyan Chowdhury, Carlos Eduardo Cancino-Chacón, Jinhua Liang, Simon Dixon and Gerhard Widmer (2024),
DExter: Learning and Controlling Performance Expression with Diffusion Models.
Applied Sciences, 14, 6543. DOI.

Yixiao Zhang, Yukara Ikemiya, Gus Xia, Naoki Murata, Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Yuki Mitsufuji, Simon Dixon (2024),
MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Models.
International Joint Conference on Artificial Intelligence, to appear.

Xavier Riley and Simon Dixon (2024),
Reconstructing the Charlie Parker Omnibook using an audio-to-score automatic transcription pipeline.
Sound and Music Computing Conference.

Alia Morsi, Huan Zhang, Akira Maezawa, Simon Dixon, and Xavier Serra (2024),
Simulating Piano Performance Mistakes for Music Learning.
Sound and Music Computing Conference (Best Paper Award).

Drew Edwards, Simon Dixon, Emmanouil Benetos, Akira Maezawa and Yuta Kusaka (2024),
A Data-Driven Analysis of Robust Automatic Piano Transcription.
IEEE Signal Processing Letters, 31, pp 681-685. DOI.

Müller, M., Dixon, S., Volk, A., Sturm, B. L. T., Rao, P., and Gotham, M. (2024),
Introducing the TISMIR Education Track: What, Why, How?.
Transactions of the International Society for Music Information Retrieval, 7(1), 85–98. DOI.

Lucas Henry, Klaus Frieler, Gabriel Solis, Martin Pfleiderer, Simon Dixon, Frank Höger, Tillman Weyde and Hélène Camille Crayencour (2024),
Dig That Lick: Exploring Patterns in Jazz with Computational Methods.
Jazzforschung / Jazz Research, 50/51, to appear.

Xavier Riley, Drew Edwards and Simon Dixon (2024),
High Resolution Guitar Transcription via Domain Adaptation.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), to appear.

Yin-Jyun Luo and Simon Dixon (2024),
Posterior Variance-Parameterised Gaussian Dropout: Improving Disentangled Sequential Autoencoders for Zero-Shot Voice Conversion.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), to appear.

Yin-Jyun Luo, Sebastian Ewert and Simon Dixon (2024),
Unsupervised Pitch-Timbre Disentanglement of Musical Instruments Using a Jacobian Disentangled Sequential Autoencoder.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), to appear.

Drew Edwards, Simon Dixon and Emmanouil Benetos (2023),
PiJAMA: Piano Jazz with Automatic MIDI Annotations.
Transactions of the International Society for Music Information Retrieval, 6(1), pp. 89–102. DOI.

Carey Bunks, Tillman Weyde, Simon Dixon and Bruno Di Giorgi (2023),
Modeling Harmonic Similarity for Jazz Using Co-occurrence Vectors and the Membrane Area.
International Society for Music Information Retrieval Conference, pp 757-764.

Xavier Riley and Simon Dixon (2023),
FiloBass: A Dataset and Corpus Based Study of Jazz Basslines.
International Society for Music Information Retrieval Conference, pp 500-507.

Huan Zhang, Emmanouil Karystinaios, Simon Dixon, Gerhard Widmer and Carlos Eduardo Cancino-Chacón (2023),
Symbolic Music Representations for Classification Tasks: A Systematic Evaluation .
International Society for Music Information Retrieval Conference, pp 848-858.

Ivan Shanin and Simon Dixon (2023),
Annotating Jazz Recordings using Lead Sheet Alignment with Deep Chroma Features .
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), DOI: 10.1109/WASPAA58266.2023.10248107.

Brendan O'Connor and Simon Dixon (2023),
A Comparative Analysis of Latent Regressor Losses for Singing Voice Conversion.
Sound and Music Computing Conference, pp 289-295.

Xavier Riley and Simon Dixon (2023),
CREPE Notes: A New Method for Segmenting Pitch Contours into Discrete Notes.
Sound and Music Computing Conference, pp 1-5.

Huan Zhang and Simon Dixon,
Disentangling the Horowitz factor: Learning content and style from expressive piano performance.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), DOI: 10.1109/ICASSP49357.2023.10095009.

Xavier Riley, Drew Edwards and Simon Dixon (2023),
Automatic Guitar Transcription with a Composable Audio-to-MIDI-to-Tablature Architecture.
Digital Music Research Network One-Day Workshop, p 11.

Huan Zhang, Jingjing Tang, Syed Rafee, Simon Dixon, George Fazekas and Geraint Wiggins (2022),
ATEPP: A Dataset of Automatically Transcribed Expressive Piano Performance.
International Society for Music Information Retrieval Conference, pp 446-453.

Yixiao Zhang, Junyan Jiang, Gus Xia and Simon Dixon (2022),
Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model.
International Society for Music Information Retrieval Conference, pp 19-26.

Yin-Jyun Luo, Sebastian Ewert and Simon Dixon (2022),
Towards Robust Unsupervised Disentanglement of Sequential Data — A Case Study Using Music Audio.
31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022), pp 3299-3305.

Polina Proutskova, Daniel Wolff, György Fazekas, Klaus Frieler, Frank Höger, Olga Velichkina, Gabriel Solis, Tillman Weyde, Martin Pfleiderer, Hélène Camille Crayencour, Geoffroy Peeters, and Simon Dixon (2022),
The Jazz Ontology: A semantic model and large-scale RDF repositories for jazz.
Journal of Web Semantics, 74, 100735. DOI.

Ruchit Agrawal, Daniel Wolff and Simon Dixon (2022),
A Convolutional-Attentional Neural Framework for Structure-Aware Performance-Score Synchronization.
IEEE Signal Processing Letters, 29, pp 344-348. DOI.

C. Lordelo, E. Benetos, S. Dixon, S. Ahlbäck and P. Ohlsson (2021),
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation.
IEEE Signal Processing Letters, 28, pp 81-85. DOI.

Emir Demirel, Sven Ahlbäck and Simon Dixon (2021),
Computational Pronunciation Analysis in Sung Utterances.
29th European Signal Processing Conference (EUSIPCO), pp 186-190.

Emir Demirel, Sven Ahlbäck and Simon Dixon (2021),
MSTRE-NET: Multistreaming Acoustic Modeling for Automatic Lyrics Transcription.
22nd International Society for Music Information Retrieval Conference (ISMIR), pp 151-158.

D. Foster and S. Dixon (2021),
Filosax: A Dataset of Annotated Jazz Saxophone Recordings.
22nd International Society for Music Information Retrieval Conference (ISMIR), pp 205-212.

C. Lordelo, E. Benetos, S. Dixon and S. Ahlbäck (2021),
Pitch-Informed Instrument Assignment Using a Deep Convolutional Network with Multiple Kernel Shapes.
22nd International Society for Music Information Retrieval Conference (ISMIR), pp 389-395.

K. O'Hanlon, E. Benetos and S. Dixon (2021),
Detecting cover songs with Key-invariant Pitch Class Networks.
2021 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp 1-6. DOI.

B. O'Connor, S. Dixon and G. Fazekas (2021),
Zero-shot Singing Technique Conversion.
15th International Symposium on Computer Music Multidisciplinary Research (CMMR).

R. Agrawal, D. Wolff and S. Dixon (2021),
Structure-Aware Audio-to-Score Alignment Using Progressively Dilated Convolutional Neural Networks.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 571-575.

E. Demirel, S. Ahlbäck and S. Dixon (2021),
Low Resource Audio-to-Lyrics Alignment from Polyphonic Music Recordings.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 586-590.

Y. Zhang, G. Xia, M. Levy and S. Dixon (2021),
COSMIC: A Conversational Interface for Human-AI Music Co-Creation. International Conference on New Interfaces for Musical Expression (NIME).

J. Pauwels, S. Dixon and J.D. Reiss (2021),
A Frontend for Adaptive Online Listening Tests.
Web Audio Conference (WAC).

Yukun Li, Emir Demirel, Polina Proutskova and Simon Dixon (2021),
Phoneme-Informed Note Segmentation of Monophonic Vocal Music.
Second Workshop on NLP for Music and Spoken Audio (NLP4MuSA).

D. Stoller, M. Tian, S. Ewert and S. Dixon (2020),
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling.
International Joint Conference on Artificial Intelligence, pp. 2893-2900.

D. Stoller, S. Ewert and S. Dixon (2020),
Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators.
International Conference on Learning Representations, April 2020.

B. O'Connor, S. Dixon and G. Fazekas (2020),
An Exploratory Study on Perceptual Spaces of the Singing Voice.
2020 Joint Conference on AI Music Creativity.

R. Agrawal and S. Dixon (2020),
Learning Frame Similarity using Siamese Networks for Audio-to-Score Alignment.
28th European Signal Processing Conference, pp 141-145.

E. Demirel, S. Ahlbäck and S. Dixon (2020),
Automatic Lyrics Transcription using Dilated Convolutional Neural Networks with Self-Attention.
International Joint Conference on Neural Networks, July 2020.

S. Mishra, E. Benetos, B.L. Sturm and S. Dixon (2020),
Reliable Local Explanations for Machine Listening.
International Joint Conference on Neural Networks, July 2020.

F. Rodríguez-Algarra, B. L. Sturm and S. Dixon (2019),
Characterising Confounding Effects in Music Classification Experiments through Interventions.
Transactions of the International Society for Music Information Retrieval, 2 (1), 52-66. DOI

A. Mehrabi, S. Dixon and M. Sandler (2019),
Vocal imitation of percussion sounds: On the perceptual similarity between imitations and imitated sounds.
PLoS ONE 14 (7): e0219955. DOI

J. Dai and S. Dixon (2019),
Intonation Trajectories within Tones in Unaccompanied Soprano, Alto, Tenor, Bass Quartet Singing.
Journal of the Acoustical Society of America, 146 (2): 1005-1014. DOI

Copyright (2019) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 146 (2), 1005-1014 and may be found at http://scitation.aip.org/content/asa/journal/jasa/146/2/10.1121/1.5120483?aemail=author.

J. Dai and S. Dixon (2019),
Pitch Accuracy and Interaction in Unaccompanied Duet Singing.
Journal of the Acoustical Society of America, 145 (2), 663-675. DOI

Copyright (2019) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 145 (2), 663-675 and may be found at http://scitation.aip.org/content/asa/journal/jasa/145/2/10.1121/1.5087817?aemail=author.

E. Benetos, S. Dixon, Z. Duan, and S. Ewert (2019),
Automatic Music Transcription: An Overview.
IEEE Signal Processing Magazine, 36 (1), 20-30. DOI

C. Weiß, M. Mauch, S. Dixon and M. Müller (2019),
Investigating style evolution of Western classical music: A computational approach.
Musicae Scientiae, 23 (4): 486-507. DOI

C. Vianna Lordelo, E. Benetos, S. Dixon and S. Ahlbäck (2019),
Investigating kernel shapes and skip connections for deep learning-based harmonic-percussive separation.
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

K. Frieler, D. Başaran, F. Höger, H.-C. Crayencour, G. Peeters and S. Dixon (2019),
Don't Hide in the Frames: Note- and Pattern-based Evaluation of Automated Melody Extraction Algorithms.
6th International Conference on Digital Libraries for Musicology, pp. 25-32. DOI

R. Agrawal and S. Dixon (2019),
A Hybrid Approach to Audio-to-Score Alignment.
Machine Learning for Music Discovery Workshop at the 36th International Conference on Machine Learning.

E. Demirel, S. Ahlbäck and S. Dixon (2019),
Exploring Generalizability of Automatic Phoneme Recognition Models.
UK Speech 2019.

S. Mishra, D. Stoller, E. Benetos, B. Sturm and S. Dixon (2019),
GAN-Based Generation and Automatic Selection of Explanations for Neural Networks.
Safe Machine Learning Workshop at the International Conference on Learning Representations.

J. Dai and S. Dixon (2019),
Understanding Intonation Trajectories and Patterns of Vocal Notes.
25th International Conference on MultiMedia Modeling, pp 243-253. DOI

M. Panteli, E. Benetos and S. Dixon (2018),
A review of manual and computational approaches for the study of world music corpora.
Journal of New Music Research, 47 (2), 176-189. DOI

K. Frieler, F. Höger, M. Pfleiderer and S. Dixon (2018),
Two Web Applications for Exploring Melodic Patterns in Jazz Solos.
19th International Society for Music Information Retrieval Conference, pp 777-783.

Eita Nakamura, Ryo Nishikimi, Simon Dixon and Kazuyoshi Yoshii (2018),
Probabilistic Sequential Patterns for Singing Transcription.
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. DOI

S. Mishra, B. Sturm and S. Dixon (2018),
Understanding Deep Machine Listening Systems through Feature Inversion.
19th International Society for Music Information Retrieval Conference, pp 755-762.

D. Stoller, S. Ewert and S. Dixon (2018),
Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation.
19th International Society for Music Information Retrieval Conference, pp 334-340.

D. Stoller and S. Ewert and S. Dixon (2018),
Jointly Detecting and Separating Singing Voice: A Multi-Task Approach.
14th International Conference on Latent Variable Analysis and Signal Separation, pp 329-339.

D. Stoller and V. Akkermans and S. Dixon (2018),
Detection of cut-points for automatic music rearrangement.
IEEE International Workshop on Machine Learning for Signal Processing.

S. Mishra, B. Sturm and S. Dixon (2018),
"What are You Listening to?" Explaining Predictions of Deep Machine Listening Systems.
26th European Signal Processing Conference, pp 2260-2264.

Eita Nakamura, Emmanouil Benetos, Kazuyoshi Yoshii, Simon Dixon (2018),
Towards Complete Polyphonic Music Transcription: Integrating Multi-Pitch Detection and Rhythm Quantization.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 101-105.

Daniel Stoller, Sebastian Ewert and Simon Dixon (2018),
Adversarial Semi-Supervised Audio Source Separation applied to Singing Voice Extraction.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 2391-2395.

Adib Mehrabi, Kuenwoo Choi, Simon Dixon and Mark Sandler (2018),
Similarity Measures for Vocal-based Drum Sample Retrieval using Deep Convolutional Auto-encoders.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 356-360.

Shengchen Li, Simon Dixon and Mark Plumbley (2018),
A demonstration of hierarchical structure usage in expressive timing analysis by model selection tests.
37th Chinese Control Conference, pp 3190-3195.

M. Panteli, E. Benetos and S. Dixon (2017),
A computational study on outliers in world music.
PLoS ONE 12 (12): e0189399 DOI

Z. Mohamad, S. Dixon and C. Harte (2017),
Pickup position and plucking point estimation on an electric guitar via autocorrelation.
Journal of the Acoustical Society of America, 142 (6), 3530-3540. DOI

Copyright (2017) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 142 (6), 3530-3540 and may be found at http://scitation.aip.org/content/asa/journal/jasa/142/6/10.1121/1.5016815?aemail=author.

B. Di Giorgi, S. Dixon, M. Zanoni, and A. Sarti (2017),
A Data-driven Model of Tonal Chord Sequence Complexity.
IEEE/ACM Transactions on Audio, Speech and Language Processing, 25 (11), 2237-2250. DOI

S. Wang, S. Ewert and S. Dixon (2017),
Identifying Missing and Extra Notes in Piano Recordings Using Score-Informed Dictionary Learning.
IEEE/ACM Transactions on Audio, Speech and Language Processing, 25 (10), 1877-1889. DOI

E. Nakamura, S. Dixon and K. Yoshii (2017),
Note Value Recognition for Piano Transcription Using Markov Random Fields.
IEEE/ACM Transactions on Audio, Speech and Language Processing, 25 (9) 1846-1858. DOI

A. Mehrabi, S. Dixon and M. Sandler (2017),
Vocal Imitation of Synthesised Sounds Varying in Pitch, Loudness and Spectral Centroid.
Journal of the Acoustical Society of America, 141 (2), 783-796. DOI

Copyright (2017) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 141 (2), pp 783-796 and may be found at http://scitation.aip.org/content/asa/journal/jasa/141/2/10.1121/1.4974825?aemail=author.

A. Mehrabi, C. Harte, C. Baume and S. Dixon (2017),
Music Thumbnailing for Radio Podcasts: A Listener Evaluation.
Journal of the Audio Engineering Society, 65 (6), 474-481.

J. Dai and S. Dixon (2017),
Analysis of Interactive Intonation in Unaccompanied SATB Ensembles.
18th International Society for Music Information Retrieval Conference (ISMIR 2017), pp 599-605.

S. Li, S. Dixon and M. Plumbley (2017),
Clustering Expressive Timing with Regressed Polynomial Coefficients Demonstrated by a Model Selection Test.
18th International Society for Music Information Retrieval Conference (ISMIR 2017), pp 457-463.

S. Mishra, B. Sturm and S. Dixon (2017),
Local Interpretable Model-Agnostic Explanations for Music Content Analysis.
18th International Society for Music Information Retrieval Conference (ISMIR 2017), pp 537-543.

V. Kedyte, M. Panteli, T. Weyde and S. Dixon (2017),
Geographical origin prediction of folk music recordings from the United Kingdom.
18th International Society for Music Information Retrieval Conference (ISMIR 2017), pp 664-670.

Z. Mohamad, S. Dixon and C. Harte (2017),
Estimating Pickup and Plucking Positions of Guitar Tones and Chords with Audio Effects.
20th International Conference on Digital Audio Effects (DAFx-17), pp 420-427.

Z. Mohamad, S. Dixon and C. Harte (2017),
Pickup Position and Plucking Point Estimation on an Electric Guitar.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 651-655.

M. Panteli, R. Bittner, J.P. Bello and S. Dixon (2017),
Towards the Characterization of Singing Styles in World Music.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 636-640.

E. Quinton, K. O'Hanlon, S. Dixon and M. Sandler (2017),
Tracking Metrical Structure Changes with Sparse-NMF.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 40-45.

S. Wang, S. Ewert and S. Dixon (2016),
Robust and Efficient Joint Alignment of Multiple Musical Performances.
IEEE/ACM Transactions on Audio, Speech and Language Processing, 24 (11), 2132-2145. DOI

S. Sigtia, E. Benetos and S. Dixon (2016),
An End-to-End Neural Network for Polyphonic Piano Music Transcription.
IEEE/ACM Transactions on Audio, Speech and Language Processing, 24 (5), pp 927-939. DOI

Y. Song, S. Dixon, M.T. Pearce and A.R. Halpern (2016),
Perceived and Induced Emotion Responses to Popular Music: Categorical and Dimensional Models,
Music Perception, 33 (4), pp 472-492. DOI

T. Cheng, M. Mauch, E. Benetos and S. Dixon (2016),
An Attack/Decay Model for Piano Transcription.
17th International Society for Music Information Retrieval Conference (ISMIR 2016), pp 584-590.

J. Dai and S. Dixon (2016),
Analysis of Vocal Imitations of Pitch Trajectories.
17th International Society for Music Information Retrieval Conference (ISMIR 2016), pp 87-93.

M. Panteli, E. Benetos and S. Dixon (2016),
Learning a Feature Space for World Music Style Similarity.
17th International Society for Music Information Retrieval Conference (ISMIR 2016), pp 538-544 (Best Student Paper Award).

M. Panteli and S. Dixon (2016),
On the Evaluation of Rhythmic and Melodic Descriptors for Music Similarity.
17th International Society for Music Information Retrieval Conference (ISMIR 2016), pp 468-474.

D. Stoller and S. Dixon (2016),
Analysis and Classification of Phonation Modes in Singing.
17th International Society for Music Information Retrieval Conference (ISMIR 2016), pp 80-86.

E. Quinton, M. Sandler and S. Dixon (2016),
Estimation of the Reliability of Multiple Rhythm Features Extraction from a Single Descriptor.
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 256-260.

M. Panteli, E. Benetos and S. Dixon (2016),
Automatic detection of outliers in world music collections.
Fourth International Conference on Analytical Approaches to World Music (AAWM).

Adib Mehrabi, Simon Dixon and Mark Sandler (2016),
Towards a Comprehensive Dataset of Vocal Imitations of Drum Sounds.
2nd AES Workshop on Intelligent Music Production, London, UK.

S. Li, S. Dixon, D. Black and M. Plumbley (2016),
A Model Selection Test for Factors Affecting the Choice of Expressive Timing Clusters for a Phrase.
Proceedings of the 13th Sound and Music Computing Conference (SMC), pp. 247-252.

P. Foster, S. Dixon and A. Klapuri (2015),
Identifying Cover Songs Using Information-Theoretic Measures of Similarity,
IEEE/ACM Transactions on Audio, Speech and Language Processing, 23 (6), pp 993-1005. DOI

J. Dai, M. Mauch and S. Dixon (2015),
Analysis of Intonation Trajectories in Solo Singing.
16th International Society for Music Information Retrieval Conference (ISMIR 2015), pp 420-426.

S. Sigtia, N. Boulanger-Lewandowski and S. Dixon (2015),
Audio Chord Recognition with a Hybrid Recurrent Neural Network.
16th International Society for Music Information Retrieval Conference (ISMIR 2015), pp 127-133.

J. Osmalskyj, J.-J. Embrechts, P. Foster and S. Dixon (2015),
Combining Features for Cover Song Identification.
16th International Society for Music Information Retrieval Conference (ISMIR 2015), pp 462-468.

R. Tubb and S. Dixon (2015),
An Evaluation of Multidimensional Controllers for Sound Design Tasks,
Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI'15), pp 47-56.

Z. Mohamad, S. Dixon and C. Harte (2015),
Digitally Moving an Electric Guitar Pickup,
18th International Conference on Digital Audio Effects (DAFx-15), pp 284-291.

T. Cheng, S. Dixon and M. Mauch (2015),
Improving Piano Note Tracking by HMM Smoothing,
European Signal Processing Conference (EUSIPCO 2015), pp 2009-2013.

Y. Song and S. Dixon (2015),
How Well Can a Music Emotion Recognition System Predict the Emotional Responses of Participants?
12th Sound and Music Computing Conference, pp 387-392.

S. Sigtia, E. Benetos, N. Boulanger-Lewandowski, T. Weyde, A.S. d'Avila Garcez and S. Dixon (2015),
A Hybrid Recurrent Neural Network for Music Transcription,
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 2061-2065.

T. Cheng, S. Dixon and M. Mauch (2015),
Modelling the Decay of Piano Sounds,
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 594-598.

S. Wang, S. Ewert and S. Dixon (2015),
Compensating for Asynchronies between Musical Voices in Score-Performance Alignment,
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 589-593 (Best Student Paper Award for the Audio and Acoustic Signal Processing track).

M. Mauch, C. Cannam, R. Bittner, G. Fazekas, J. Salamon, J. Dai, J. Bello and S. Dixon (2015),
Computer-aided Melody Note Transcription Using the Tony Software: Accuracy and Efficiency.
First International Conference on Technologies for Music Notation and Representation (TENOR 2015), pp 23-30.

T. Wilmering, S. Bechhofer, S. Dixon, G. Fazekas and K. Page (2015),
Automating Annotation of Media with Linked Data Workflows,
Third International Workshop on Linked Media (LiME 2015), pp 737-738.

T. Wilmering, G. Fazekas, S. Dixon, K. Page and S. Bechhofer (2015),
Towards High Level Feature Extraction from Large Live Music Recording Archives,
Machine Learning for Music Discovery Workshop, 32nd International Conference on Machine Learning.

D. Tidhar, S. Dixon, E. Benetos and T. Weyde (2014),
The Temperament Police,
Early Music, 42 (4), pp 579-590. DOI

P. Foster, M. Mauch and S. Dixon (2014),
Sequential Complexity as a Descriptor for Musical Similarity,
IEEE/ACM Transactions on Audio, Speech and Language Processing, 22 (12), pp 1965-1977. DOI

M. Mauch, K. Frieler and S. Dixon (2014),
Intonation in Unaccompanied Singing: Accuracy, Drift and a Model of Reference Pitch Memory,
Journal of the Acoustical Society of America, 136 (1), pp 401-411. DOI

Copyright (2014) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 136 (1), pp 401-411 and may be found at http://scitation.aip.org/content/asa/journal/jasa/136/1/10.1121/1.4881915?aemail=author.

R. Tubb and S. Dixon (2014),
A Zoomable Mapping of a Musical Parameter Space Using Hilbert Curves ,
Computer Music Journal, 38 (3), pp 23-33. DOI

W. Goebl, S. Dixon and E. Schubert (2014),
Quantitative Methods: Motion Analysis, Audio Analysis, and Continuous Response Techniques,
in Expressiveness in Music Performance: Empirical Approaches across Styles and Cultures, Ed. D. Fabian, R. Timmers and E. Schubert, Oxford University Press, pp. 221-239.

D. Stowell and S. Dixon (2014),
Integration of informal music technologies in secondary school music lessons.
British Journal of Music Education, 31 (1), pp 19-39. DOI

Copyright (2013) Cambridge University Press. The article appeared in the British Journal of Music Education.

T. Cheng, S. Dixon and M. Mauch (2014)
A Comparison of Extended Source-Filter Models for Musical Signal Reconstruction.
17th International Conference on Digital Audio Effects, pp 203-209.

H. Kirchhoff, R. Badeau and S. Dixon (2014),
Towards Complex Matrix Decomposition of Spectrograms based on the Relative Phase Offsets of Harmonic Sounds.
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 1572-1576.

M. Mauch and S. Dixon (2014),
PYIN: a Fundamental Frequency Estimator Using Probabilistic Threshold Distributions,
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 659-663. DOI

S. Sigtia and S. Dixon (2014),
Improved Music Feature Learning With Deep Neural Networks,
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 6959-6963. DOI

S. Sigtia, E. Benetos, S. Cherla, T. Weyde, A. Garcez and S. Dixon (2014),
An RNN-based Music Language Model for Improving Automatic Music Transcription,
15th International Society for Music Information Retrieval Conference, pp 53-58.

L. Thompson, S. Dixon and M. Mauch (2014),
Drum Transcription via Classification of Bar-level Rhythmic Patterns,
15th International Society for Music Information Retrieval Conference, pp 187-192.

S. Wang, S. Ewert and S. Dixon (2014),
Robust Joint Alignment of Multiple Versions of a Piece of Music,
15th International Society for Music Information Retrieval Conference, pp 83-88.

R. Tubb and S. Dixon (2014),
The Divergent Interface: Supporting Creative Exploration of Parameter Spaces,
14th International Conference on New Interfaces for Musical Expression.

R. Tubb and S. Dixon (2014),
A Four Strategy Model of Creative Parameter Space Interaction,
5th International Conference on Computational Creativity.

T. Weyde, S. Cottrell, E. Benetos, D. Wolff, D. Tidhar, J. Dykes, M. Plumbley, S. Dixon, M. Barthet, N. Gold, S. Abdallah, M. Mahey (2014),
Digital Music Lab - A Framework for Analysing Big Music Data,
European Conference on Data Analysis, Workshop on Statistical Musicology ( abstract only).

T. Weyde, S. Cottrell, J. Dykes, E. Benetos, D. Wolff, D. Tidhar, N. Gold, S. Abdallah, M. Plumbley, S. Dixon, M. Barthet, M. Mahey, A. Tovell, A. Alancar-Brayner (2014),
Big Data for Musicology,
1st International Digital Libraries for Musicology Workshop.

C. Weiß, M. Mauch and S. Dixon (2014),
Timbre-invariant Audio Features for Style Analysis of Classical Music,
Joint 40th International Computer Music Conference and 11th Sound and Music Computing Conference, pp 1461-1468.

E. Benetos and S. Dixon (2013),
Multiple-instrument Polyphonic Music Transcription using a Temporally-constrained Shift-invariant Model.
Journal of the Acoustical Society of America, 133 (3), pp 1727-1741. DOI

Copyright (2013) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 131 (3), pp 1727-1741 and may be found at http://link.aip.org/link/?JAS/133/1727">

E. Benetos, S. Dixon, D. Giannoulis, H. Kirchhoff and A. Klapuri (2013),
Automatic Music Transcription: Challenges and Future Directions.
Journal of Intelligent Information Systems, 41 (3), pp 407-434. DOI

X. Serra, M. Magas, E. Benetos, M. Chudy, S. Dixon, A. Flexer, E. Gómez, F. Gouyon, P. Herrera, S. Jorda, O. Paytuvi, G. Peeters, J. Schlüter, H. Vinet and G. Widmer (2013),
Roadmap for Music Information Research.
Final report of the EU FP7 MIReS Project.

T. Cheng, S. Dixon and M. Mauch (2013),
A Deterministic Annealing EM Algorithm for Automatic Music Transcription.
In 14th International Society for Music Information Retrieval Conference, pp 475-480.

Y. Song, S. Dixon, M. Pearce and A. Halpern (2013),
Do Online Social Tags Predict Perceived or Induced Emotional Responses to Music?
In 14th International Society for Music Information Retrieval Conference, pp 89-94.

H. Kirchhoff, S. Dixon and A. Klapuri (2013),
Multiple instrument tracking based on reconstruction error, pitch continuity and instrument activity.
In 10th International Symposium on Computer Music Multidisciplinary Research, pp 894-903 (Best Poster Paper Award).

Y. Song, S. Dixon, M. Pearce and G. Fazekas (2013),
Using Tags to Select Stimuli in the Study of Music and Emotion.
Proceedings of the 3rd International Conference on Music and Emotion.

P. Foster, S. Dixon and A. Klapuri (2013),
Identification of Cover Songs using Information Theoretic Measures of Similarity.
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 739-743.

H. Kirchhoff, S. Dixon and A. Klapuri (2013),
Missing Template Estimation for User-assisted Music Transcription.
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 26-30.

M. Chudy, A. Perez Carrillo and S. Dixon (2013),
On the Relation between Gesture, Tone Production and Perception in Classical Cello Performance.
Proceedings of Meetings on Acoustics 19 (1), 035017. Presented at the 21st International Congress on Acoustics.

M. Chudy and S. Dixon (2013),
Recognising Cello Performers Using Timbre Models (preprint).
In B. Lausen, D. van den Poel, and A. Ultsch, editors, Joint Annual Conference of the German Association for Pattern Recognition (DAGM) and the German Classification Society (GfKl), and Symposium of the International Federation of Classification Societies (IFCS): Algorithms from & for Nature and Life, Studies in Classification, Data Analysis, and Knowledge Organization, Heidelberg: Springer, pp 511-518.

A. Allik, G. Fazekas, S. Dixon, and M. Sandler (2013),
Facilitating Music Information Research with Shared Open Vocabularies.
Extended Semantic Web Conference (ESWC), pp 178-183. (DOI)

A. Allik, G. Fazekas, S. Dixon, and M. Sandler (2013),
A Shared Vocabulary for Audio Features.
Extended Semantic Web Conference (ESWC), pp 285-286. (DOI)

S. Dixon, M. Mauch and D. Tidhar (2012),
Estimation of Harpsichord Inharmonicity and Temperament from Musical Recordings.
Journal of the Acoustical Society of America, 131 (1), pp 878-887.

Copyright (2012) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The article appeared in the Journal of the Acoustical Society of America, 131 (1), pp 878-887 and may be found at http://link.aip.org/link/?JAS/131/878

E. Benetos and S. Dixon (2012),
A shift-invariant latent variable model for automatic music transcription.
Computer Music Journal, 36 (4), pp 81-94. DOI

A. Arzt, G. Widmer, and S. Dixon (2012),
Adaptive distance normalization for real-time music tracking.
In 20th European Signal Processing Conference, pp 2689-2693.

E. Benetos and S. Dixon (2012),
Temporally-constrained Convolutive Probabilistic Latent Component Analysis for Multi-pitch Detection.
International Conference on Latent Variable Analysis and Signal Separation, pp 364-371.

E. Benetos, A. Klapuri and S. Dixon (2012),
Score-informed transcription for automatic piano tutoring.
In 20th European Signal Processing Conference, pp 2153-2157.

Emmanouil Benetos, Mathieu Lagrange, and Simon Dixon (2012),
Characterisation of acoustic scenes using a temporally-constrained shift-invariant model.
In 15th International Conference on Digital Audio Effects, pp 317-323.

Emmanouil Benetos, Simon Dixon, Dimitrios Giannoulis, Holger Kirchhoff, and Anssi Klapuri (2012),
Automatic music transcription: Breaking the glass ceiling.
In 13th International Society for Music Information Retrieval Conference, pp 379-384.

P. Foster, A. Klapuri, and S. Dixon (2012),
A method for identifying repetition structure in musical audio based on time series prediction.
In 20th European Signal Processing Conference, pp 1299-1303.

J. Gansemann, P. Scheunders, and S. Dixon (2012),
Improving PLCA-based score-informed source separation with invertible constant-Q transforms.
In 20th European Signal Processing Conference, pp 2634-2638.

H. Kirchhoff, S. Dixon and A. Klapuri (2012),
Shift-Variant Non-Negative Matrix Deconvolution for Music Transcription.
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp 125-128.

Holger Kirchhoff, Simon Dixon, and Anssi Klapuri (2012),
Multi-template shift-variant non-negative matrix deconvolution for semi-automatic music transcription.
In 13th International Society for Music Information Retrieval Conference, pp 415-420.

R. Macrae and S. Dixon (2012),
Ranking lyrics for online search.
In 13th International Society for Music Information Retrieval Conference, pp 361-366.

M. Mauch and S. Dixon (2012),
A corpus-based study of rhythm patterns.
In 13th International Society for Music Information Retrieval Conference, pp 163-168.

M. Barthet, G. Fazekas, S. Dixon and M. Sandler (2012),
Social Media Retrieval for Music Education.
In Digital Futures 2012: The Third Annual Digital Economy All Hands Conference.

Y. Song, M. Pearce, and S. Dixon (2012),
A survey of music recommendation systems and future perspectives.
In 9th International Symposium on Computer Music Modelling and Retrieval, pages 395-410, 2012.

Y. Song, M. Pearce, and S. Dixon (2012),
Evaluation of musical features for emotion classification.
In 13th International Society for Music Information Retrieval Conference, pp 523-528.

M.J. Terrill, G. Fazekas, A.J.R. Simpson, J. Smith, and S. Dixon (2012),
Listening level changes music similarity.
In 13th International Society for Music Information Retrieval Conference, pp 487-492.

R. Tubb, A. Klapuri, and S. Dixon (2012),
The Wablet: Scanned synthesis on a multi-touch interface.
In 15th International Conference on Digital Audio Effects, pp 279-286.

S. Dixon, M. Mauch and A. Anglade (2011),
Probabilistic and Logic-Based Modelling of Harmony.
CMMR 2010 Post Symposium Proceedings, Ed. R. Kronland-Martinet, S. Ystad, K. Jensen and M. Aramaki, Springer LNCS 6684, Heidelberg, pp 1-19.

S. Dixon, D. Tidhar and E. Benetos (2011),
The Temperament Police: The Truth, the Ground Truth and Nothing but the Truth.
In 12th International Society for Music Information Retrieval Conference, pp 281-286.

R. Macrae and S. Dixon (2011),
Guitar Tab Mining, Analysis and Ranking.
In 12th International Society for Music Information Retrieval Conference, pp 453-458.

D. Stowell and S. Dixon (2011),
MIR in School? Lessons from Ethnographic Observation of Secondary School Music Classes.
In 12th International Society for Music Information Retrieval Conference, pp 347-352.

M. Barthet and S. Dixon,
Ethnographic Observations of Musicologists at the British Library: Implications for Music Information Retrieval.
In 12th International Society for Music Information Retrieval Conference, pp 353-358.

E. Benetos and S. Dixon (2011),
Joint Multi-Pitch Detection using Spectral Envelope Estimation for Polyphonic Music Transcription.
Journal of Selected Topics in Signal Processing, 5 (6), pp 1111-1123.

E. Benetos and S. Dixon (2011),
A Temporally-Constrained Convolutive Probabilistic Model for Pitch Detection.
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp 133-136.

E. Benetos and S. Dixon (2011),
Polyphonic Music Transcription using Note Onset and Offset Detection.
IEEE International Conference on Acoustics, Speech and Signal Processing, pp 37-40.

E. Benetos and S. Dixon (2011),
Multiple-Instrument Polyphonic Music Transcription using a Convolutive Probabilistic Model.
8th Sound and Music Computing Conference, pp 19-24.

L.Mearns, E. Benetos and S. Dixon (2011),
Automatically Detecting Key Modulations in J.S. Bach Chorale Recordings.
8th Sound and Music Computing Conference, pp 25-32.

R. Macrae, J. Neumann, X. Anguera, N. Oliver and S. Dixon (2011),
Real-Time Synchronisation of Multimedia Streams in a Mobile Device.
IEEE International Conference on Multimedia and Expo, Workshop on Advances in Music Information Research (AdMIRe).

C. Mesnage, A. Rafiq, S. Dixon and R. Brixtel (2011),
Music Discovery with Social Networks.
Workshop on Music Recommendation and Discovery, Chicago, USA, pp 1-6.

S. Dixon, M. Sandler, M. d’Inverno, and C. Rhodes (2010),
Towards a distributed research environment for music informatics and computational musicology.
Journal of New Music Research, 39 (4): 291-294.

A. Anglade, E. Benetos, M. Mauch, and S. Dixon (2010),
Improving music genre classification using automatically induced harmony rules .
Journal of New Music Research, 39 (4), 349-361.

E. Benetos and S. Dixon (2010),
Multiple-F0 estimation of piano sounds exploiting spectral structure and temporal evolution.
In 2010 Workshop on Statistical and Perceptual Audition (SAPA), 2010.

M. Chudy and S. Dixon (2010),
Towards music performer recognition using timbre features.
In Third International Conference of Students of Systematic Musicology.

S. Dixon (2010),
Computational modelling of harmony.
In 7th International Symposium on Computer Music Modeling and Retrieval, (CMMR 2010), Malaga, Spain.

K. Jacobson, S. Dixon, and M. Sandler (2010),
LinkedBrainz: Providing the MusicBrainz next generation schema as linked data.
Late-breaking session, 11th International Society for Music Information Retrieval Conference, Utrecht, Netherlands.

R. Macrae and S. Dixon (2010),
A guitar tablature score follower.
In IEEE International Conference on Multimedia and Expo.

R. Macrae and S. Dixon (2010),
Accurate real-time windowed time warping.
In 11th International Society for Music Information Retrieval Conference.

M. Mauch and S. Dixon (2010),
Simultaneous estimation of chords and musical context from audio.
IEEE Transactions on Audio, Speech and Language Processing, 18 (6), 1280-1289. DOI: 10.1109/TASL.2009.2032947

M. Mauch and S. Dixon (2010),
Approximate Note Transcription for the Improved Identification of Difficult Chords.
In 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, Netherlands.

L. Mearns and S. Dixon (2010),
Characterisation of composer style using high level musical features.
Late-breaking session, 11th International Society for Music Information Retrieval Conference, Utrecht, Netherlands.

L. Mearns, D. Tidhar, and S. Dixon (2010),
Characterisation of composer style using high-level musical features.
In 3rd ACM Workshop on Machine Learning and Music.

L. Mearns and S. Dixon (2010),
How do you characterise musical style?
In Third International Conference of Students of Systematic Musicology, 2010.

D. Tidhar, M. Mauch, and S. Dixon (2010),
High precision frequency estimation for harpsichord tuning classification.
In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pages 61-64.

D. Tidhar, G. Fazekas, M. Mauch, and S. Dixon (2010),
TempEst: Harpsichord temperament estimation in a semantic-web environment.
Journal of New Music Research, 39 (4), 327-336.

D. Tidhar, G. Fazekas, M. Mauch, and S. Dixon (2010),
Temperament estimation as an MIR task.
Late-breaking session, 11th International Society for Music Information Retrieval Conference, Utrecht, Netherlands.

A. Anglade and S. Dixon (2009),
First-order logic classification models of musical genres based on harmony.
In 6th Sound and Music Computing Conference, pages 309-314.

A. Anglade, R. Ramirez, and S. Dixon (2009),
Genre classification using harmony rules induced from automatic chord transcriptions.
In 10th International Society for Music Information Retrieval Conference, pages 669-674.

M. Mauch, K. Noland, and S. Dixon (2009),
Using musical structure to enhance automatic chord transcription.
In 10th International Society for Music Information Retrieval Conference, pages 231-236.

M. Mauch, C. Cannam, M. Davies, S. Dixon, C. Harte, S. Kolozali, and D. Tidhar (2009),
OMRAS-2 metadata project 2009.
Late-breaking session, 10th International Society for Music Information Retrieval Conference, Kobe, Japan.

A. Anglade, S. Dixon (2008),
Characterisation of Harmony with Inductive Logic Programming.
Proceedings of the 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, USA, pp 63-68.

A. Anglade, S. Dixon (2008),
Towards Logic-based Representations of Musical Harmony for Classification, Retrieval and Knowledge Discovery.
Proceedings of the International Workshop on Machine Learning and Music (MML2008 held in conjunction with ICML/COLT/UAI 2008), Helsinki, Finland, July, 2008.

M. Mauch, S. Dixon (2008),
A Discrete Mixture Model for Chord Labelling.
Proceedings of the 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, USA.

M. Mauch, D. Müllensiefen, S. Dixon, G. Wiggins (2008),
Can Statistical Language Models be Used for the Analysis of Harmonic Progressions?
Proceedings of the 10th International Conference on Music Perception and Cognition, Sapporo, Japan.

M. Mauch, D. Müllensiefen, S. Dixon, G. Wiggins (2008),
Applying Tools from Natural Language Processing Analysis to Harmony: A Bottom Up Approach.
Conference on Music, Language and the Mind.

R. Macrae, S. Dixon (2008),
From Toy to Tutor: Note-Scroller is a Game to Teach Music.
8th International Conference on New Interfaces for Musical Expression.

A. Arzt, G. Widmer, S. Dixon (2008),
Automatic Page Turning for Musicians via Real-Time Machine Listening.
Proceedings of the 18th European Conference on Artificial Intelligence, pp 241-245.

G. Widmer, S. Dixon, P. Knees, E. Pampalk, T. Pohle (2008),
From Sound to Sense via Feature Extraction and Machine Learning: Deriving High-Level Descriptors for Characterising Music.
Sound to Sense - Sense to Sound: A State of the Art in Sound and Music Computing, Ed. P. Polotti and D. Rocchesso, pp 161-194.

W. Goebl, S. Dixon, G. De Poli, A. Friberg, R. Bresin, G. Widmer (2008),
Sense in Expressive Music Performance: Data Acquisition, Computational Studies, and Models.
Sound to Sense - Sense to Sound: A State of the Art in Sound and Music Computing, Ed. P. Polotti and D. Rocchesso, pp 195-242.

S. Dixon (2007),
Evaluation of the Audio Beat Tracking System BeatRoot.
Journal of New Music Research, 36, 1, pp 39-50.

M. Mauch, S. Dixon, C. Harte, M. Casey, B. Fields
Discovering Chord Idioms Through Beatles and Real Book Songs.
Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, September 2007, pp 111-114.

S. Dixon,
Tools for Analysis of Musical Expression.
Proceedings of the 19th International Congress on Acoustics, Madrid, September 2007.

F. Gouyon, S. Dixon and G. Widmer,
Evaluating low-level features for beat classification and tracking.
Proceedings of the 2007 International Conference on Acoustics, Speech and Signal Processing, Vol. IV, pp 1309-1312.

S. Dixon, W. Goebl and E. Cambouropoulos (2006),
Perceptual Smoothness of Tempo in Expressively Performed Music.
Music Perception, 23 (3), pp 195-214.

F. Gouyon, A. Klapuri, S. Dixon, M. Alonso, G. Tzanetakis, C. Uhle and P. Cano (2006),
An Experimental Comparison of Audio Tempo Induction Algorithms.
IEEE Transactions on Audio, Speech and Language Processing, 14 (5), pp 1832-1844.

S. Dixon
Onset Detection Revisited
Proceedings of the 9th International Conference on Digital Audio Effects, Montreal, September 2006, pp 133-137.

A. Flexer, F. Gouyon, S. Dixon and G. Widmer,
Probabilistic Combination of Features for Music Classification,
Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria BC, October 2006, pp 111-114.

S. Dixon,
Computer Analysis of Performance Timing,
9th International Conference on Music Perception and Cognition, Bologna, August 2006.

F. Gouyon and S. Dixon,
A Review of Automatic Rhythm Description Systems.
Computer Music Journal, 29 (1), 2005, pp 34-54. DOI

S. Dixon,
An On-Line Time Warping Algorithm for Tracking Musical Performances,
Proceedings of the International Joint Conference on Artificial Intelligence, Edinburgh, August 2005, pp 1727-1728.

S. Dixon,
Live Tracking of Musical Performances using On-Line Time Warping,
Proceedings of the 8th International Conference on Digital Audio Effects (DAFx05), Madrid, Spain, September 2005, pp 92-97.

S. Dixon and G. Widmer,
MATCH: A Music Alignment Tool Chest,
6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, September 2005, pp 492-497. (Best Poster Award)

S. Dixon, W. Goebl and G. Widmer,
The 'Air Worm': An Interface for Real-Time Manipulation of Expressive Music Performance,
Proceedings of the 2005 International Computer Music Conference (ICMC2005), Barcelona, Spain, September 2005, pp 614-617.

G. Widmer, S. Dixon, A. Flexer, W. Goebl, P. Knees, S.T. Madsen, E. Pampalk, T. Pohle, M. Schedl and A. Tobudic
The Maching Learning and Intelligent Music Processing Group at the Austrian Research Institute for Artificial Intelligence (OFAI),
Proceedings of the 2005 International Computer Music Conference (ICMC2005), Barcelona, Spain, September 2005, pp 169-172.

W. Goebl, S. Dixon, G. DePoli, A. Friberg, R. Bresin and G. Widmer
'Sense' in Expressive Music Performance: Data Acquisition, Computational Studies, and Models,
S2S2 Summer School, Genova, 2005.

S. Dixon
Audio Analysis Applications for Music.
Encyclopedia of Information Science and Technology, (ed. M.Khosrow-Pour), Idea Group, 2005, pp 188-196.

E. Pampalk and S. Dixon and G. Widmer,
Exploring Music Collections by Browsing Different Views.
Computer Music Journal, 28 (2), 2004, pp 49-62.

S. Dixon, F. Gouyon and G. Widmer,
Towards Characterisation of Music via Rhythmic Patterns,
5th International Conference on Music Information Retrieval (ISMIR 2004), pp 509-516.

F. Gouyon and S. Dixon,
Dance Music Classification: A Tempo-Based Approach,
5th International Conference on Music Information Retrieval (ISMIR 2004), pp 501-504.

F. Gouyon, N. Wack and S. Dixon,
An Open Source Tool for Semi-Automatic Rhythmic Annotation.
Proceedings of the 7th International Conference on Digital Audio Effects, 2004, pp 193-196.

F. Gouyon, S. Dixon, E. Pampalk and G. Widmer,
Evaluating Rhythmic Descriptors for Musical Genre Classification.
Proceedings of the AES 25th International Conference, London, June 2004, pp 196-204.

S. Dixon
Analysis of Musical Content in Digital Audio.
Computer Graphics and Multimedia: Applications, Problems, and Solutions (ed. J. DiMarco), Idea Group, 2004, pp 214-235.

G. Widmer, S. Dixon, W. Goebl, E. Pampalk and A. Tobudic
In Search of the Horowitz Factor.
AI Magazine, 24 (3), 2003, pp 111-130.

S. Dixon, E. Pampalk and G. Widmer,
Classification of Dance Music by Periodicity Patterns.
4th International Conference on Music Information Retrieval (ISMIR 2003), Baltimore MD, October 2003, pp 159 - 165.

E. Pampalk, S. Dixon and G. Widmer
Exploring Music Collections by Browsing Different Views.
4th International Conference on Music Information Retrieval (ISMIR 2003), Baltimore MD, October 2003, pp 201 - 208.

E. Pampalk, S. Dixon and G. Widmer
On the Evaluation of Perceptual Similarity Measures for Music.
6th International Conference on Digital Audio Effects (DAFx-03), London, UK, September 2003, pp 7-12.

S. Dixon
On the Analysis of Musical Expression in Audio Signals.
Storage and Retrieval for Media Databases 2003, SPIE-IS&T Electronic Imaging, SPIE Vol. 5021, pp 122-132.

S. Dixon
(PDF)
Towards Automatic Analysis of Expressive Performance.
5th Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM5), 8 - 13 September 2003, Hanover, Germany, pp 107-110.

S. Dixon, W. Goebl and G. Widmer
The Performance Worm: Real Time Visualisation of Expression Based on Langner's Tempo-Loudness Animation.
International Computer Music Conference, 16 - 21 September 2002, Göteborg, Sweden, pp 361-364.

S. Dixon, W. Goebl and G. Widmer
Real Time Tracking and Visualisation of Musical Expression.
II International Conference on Music and Artificial Intelligence, 12 - 15 September 2002, Edinburgh, Scotland, pp 58-68.

S. Dixon and W. Goebl
Pinpointing the Beat: Tapping to Expressive Performances.
7th International Conference on Music Perception and Cognition (ICMPC7), 17 - 21 July 2002, Sydney, Australia, pp 617-620.

S. Dixon.
Automatic Extraction of Tempo and Beat from Expressive Performances.
Journal of New Music Research, 30 (1), 2001, pp 39-58.

  • Download BeatRoot software (requires Java 1.5 or higher)
  • Audio beat tracking examples
    • MP3 files (~100kB each):   1,  2,  3,  4,  5,  6
    • WAV files (~1-2MB each):   1,  2,  3,  4,  5,  6
  • MIDI beat tracking examples
    • MP3 files (~100kB each):   1,  2,  3
    • WAV files (~1-2MB each):   1,  2,  3

S. Dixon.
An Interactive Beat Tracking and Visualisation System.
Proceedings of the International Computer Music Conference, Havana, Cuba, 2001, pp 215-218.

E. Cambouropoulos, S. Dixon, W. Goebl and G. Widmer.
Human Preferences for Tempo Smoothness.
VII International Symposium on Systematic and Comparative Musicology, III International Conference on Cognitive Musicology, 16 - 19 August 2001, Jyväskylä, Finland, pp 18-26.

W. Goebl and S. Dixon.
Analysis of Tempo Classes in Performances of Mozart Sonatas.
VII International Symposium on Systematic and Comparative Musicology, III International Conference on Cognitive Musicology, 16 - 19 August 2001, Jyväskylä, Finland, pp 65-76.

S. Dixon.
An Empirical Comparison of Tempo Trackers.
8th Brazilian Symposium on Computer Music, 31 July - 3 August 2001, Fortaleza, Brazil, pp 832-840.

S. Dixon, W. Goebl and E. Cambouropoulos.
Beat Extraction from Expressive Musical Performances.
2001 meeting of the Society for Music Perception and Cognition (SMPC2001), 9 - 11 August 2001, Kingston, Ontario, Canada, pp 62-63.
Technical report OFAI-TR-2001-22

S. Dixon.
Learning to Detect Onsets of Acoustic Piano Tones.
MOSART Workshop on Current Research Directions in Computer Music, 15 - 17 November 2001, Barcelona, Spain.

G. Widmer, S. Dixon, W. Goebl, E. Stamatatos and A. Tobudic.
Empirical Music Performance Research: OeFAI's Position.
MOSART Workshop on Current Research Directions in Computer Music, 15 - 17 November 2001, Barcelona, Spain.

S. Dixon.
A Lightweight Multi-Agent Musical Beat Tracking System.
PRICAI 2000: Proceedings of the Pacific Rim International Conference on Artificial Intelligence,
Melbourne, Australia, 2000, pp 778-788.

S. Dixon and E. Cambouropoulos.
Beat Tracking with Musical Knowledge.
ECAI 2000: Proceedings of the 14th European Conference on Artificial Intelligence,
ed. W.Horn, IOS Press, Amsterdam, 2000, pp 626-630.

S. Dixon.
Extraction of Musical Performance Parameters from Audio Data.
IEEE Pacific-Rim Conference on Multimedia,
Sydney, Australia, December 2000, pp 42-45.

S. Dixon.
On the Computer Recognition of Solo Piano Music.
Mikropolyphonie, 6, 2000.
An earlier version appeared in:
Interfaces: Australasian Computer Music Conference,
Brisbane, Australia, 2000, pp 31-37.
Sound examples: MP3 files (~80kB) and WAV files (~1MB):

  • Mozart Piano Sonata K.332 (2nd movt):   Original   (MP3)   (WAV)   Transcribed   (MP3)   (WAV)
  • Mozart Piano Sonata K.279 (2nd movt):   Original   (MP3)   (WAV)   Transcribed   (MP3)   (WAV)
  • Mozart Piano Sonata K.281 (3rd movt):   Original   (MP3)   (WAV)   Transcribed   (MP3)   (WAV)

S. Dixon.
A Beat Tracking System for Audio Signals.
Proceedings of the Conference on Mathematical and Computational Methods in Music,
Vienna, Austria, December 1999, pp 101-110.
Sound examples: the beat tracking system inserts a cowbell sample at each calculated beat time.
MP3 files (80kB each):   1, 2, 3.
WAV files (880kB each):   1, 2, 3.

S. Dixon.
Beat Induction and Rhythm Recognition.
Proceedings of the Australian Joint Conference on Artificial Intelligence,
Perth, Australia, 1997, pp 311-320.

S. Dixon.
A Dynamic Modelling Approach to Music Recognition.
Proceedings of the International Computer Music Conference,
Hong Kong, 1996, pp 83-86.

S. Dixon.
Multiphonic Note Identification.
Australian Computer Science Communications, 18, 1,
Proceedings of the 19th Australasian Computer Science Conference,
Melbourne, Australia, 1996, pp 318-323.

S. Dixon, D. M. W. Powers.
The Characterisation, Separation and Transcription of Complex Acoustic Signals.
Proceedings of the Sixth Australian International Conference on Speech Science and Technology,
Adelaide, Australia, 1996, pp 73-78.

D. M. W. Powers, C. R. Clark, S. Dixon, D. L. Weber.
Cocktails and Brainwaves: Experiments with Complex and Subliminal Auditory Stimuli.
Proceedings of the Australian and New Zealand Conference on Intelligent Information Systems,
Adelaide, Australia, 1996, pp 68-71.

S. Dixon, W. R. Wobcke.
A Nonmonotonic Reasoning Belief Revision System.
Australian Computer Science Communications, 17, 1,
Proceedings of the 18th Australasian Computer Science Conference,
Adelaide, Australia, 1995, pp 151-160.

S. Dixon.
Belief Revision: A Computational Approach.   (PDF)   (PS)
Unpublished PhD thesis, Basser Department of Computer Science,
University of Sydney, Australia, 1994.

S. Dixon, W. R. Wobcke.
The implementation of a first-order logic AGM belief revision system.
  (PS)
Proceedings of 5th IEEE International Conference on Tools with AI,
Boston MA, pages 40--47.
IEEE Computer Society Press, 1993.

S. Dixon, N. Y. Foo.
Connections between the ATMS and AGM belief revision.
Proceedings of 13th International Joint Conference on Artificial Intelligence,
Chambery, France, pages 534-539.
Morgan Kaufmann, 1993.

S. Dixon.
A finite base belief revision system.
Australian Computer Science Communications, 15(1):445-451.
Proceedings of ACSC-16: 16th Australian Computer Science Conference,
Brisbane, Australia, January 1993.
Queensland University of Technology, Brisbane, Australia, 1993.

S. Dixon, N. Y. Foo.
Beyond foundational reasoning.
Proceedings of AI'92: 5th Australian Joint Conference on Artificial Intelligence,
Hobart, Australia, pages 247-252.
World Scientific, Singapore, 1992.

S. Dixon, N. Y. Foo.
Encoding the ATMS in AGM logic (revised).
Technical Report 441, Basser Department of Computer Science,
University of Sydney, Australia, 1992.

N. Y. Foo, S. Dixon, D. Kuo.
Systems Dynamics via Theory Revision.
Open Distributed Processing Workshop Proceedings,
University of Sydney, Australia, 1990.

R. Colomb, S. Dixon.
Database Implementation of an Artificial Intelligence Programming Paradigm.
Proceedings of AI'90: 4th Australian Joint Conference on Artificial Intelligence,
Perth, Australia, pp 462-473,
World Scientific Press, Singapore, 1990.

Research Staff & Students

Sungkyun Chang
(Research assistant) 		Music Performance Assessment and Feedback
Yukun Li
(PhD student, co-supervised by Polina Proutskova) 		Segmenting and Analysing Pitch Contours across Singing Styles
Mary Pilataki-Manika
(PhD student on the AIM CDT, co-supervised by Matthias Mauch, in collaboration with Apple Music) 		Polyphonic Music Transcription using Deep Learning
Dave Foster
(PhD student on the AIM CDT) 		Modelling the Creative Process of Jazz Improvisation
Yin-Jyun Luo
(PhD student on the AIM CDT, co-supervised by Sebastian Ewert, in collaboration with Spotify) 		Industry-scale Machine Listening for Music and Audio Data
Xavier Riley
(PhD student on the AIM CDT) 		Transcribing the Jazz Ensemble: Applying Deep Learning Models to Jazz Transcription
Huan Zhang
(PhD student on the AIM CDT) 		Computational Modelling of Expressive Piano Performance
Drew Edwards
(PhD student on the AIM CDT, co-supervised by Akira Maezawa, in collaboration with Yamaha) 		Modeling Jazz Piano: Symbolic Music Generation via Large-Scale Automatic Transcription
Carey Bunks
(PhD student on the AIM CDT, co-supervised by Bruno di Giorgi, in collaboration with Apple) 		Cover Song Identification for Jazz
Tyler McIntosh
(PhD student on the AIM CDT, co-supervised by Nadine Kroher, in collaboration with DAACI) 		Performance Rendering for Music Generation Systems
Ningzhi Wang
(PhD student on the AIM CDT, in collaboration with Spotify) 		Generative Models for Music Audio Representation and Understanding
Nicolas Guo
(PhD student on the AIM CDT) 		Towards Comprehensive Automatic Guitar Transcription via a Multi-modal Approach
Ivan Shanin Modeling Melodic Jazz Improvisation

Completed PhDs

Yixiao Zhang
(completed Nov 2024) 		Improving Controllability and Editability for Pretrained Text-to-Music Generation Models
(PhD student in the UKRI Centre for Doctoral Training in AI and Music (AIM), in collaboration with Apple, co-supervised by Mark Levy)
Brendan O'Connor
(completed March 2024) 		Analysis, Disentanglement, and Conversion of Singing Voice Attributes
(part of the Media and Arts Technology (MAT) Centre for Doctoral Training)
Carlos Vianna Lordelo
(completed Nov 2023) 		Deep Learning Methods for Instrument Separation and Recognition
(part of the MIP-Frontiers project, in collaboration with DoReMIR Music Research, and co-supervised by Emmanouil Benetos)
Emir Demirel
(completed June 2022) 		Deep Neural Networks for Automatic Lyrics Transcription
(part of the MIP-Frontiers project, in collaboration with DoReMIR Music Research)
Ruchit Agrawal
(completed May 2022) 		Towards Context-Aware Neural Performance-Score Synchronisation
(part of the MIP-Frontiers project, in collaboration with Tido Music)
Saumitra Mishra
(completed Sept 2020) 		Interpretable Machine Learning for Machine Listening
(co-supervisor: Bob Sturm, KTH)
Daniel Stoller
(completed July 2020) 		Deep Learning for Music Information Retrieval in Limited Data Scenarios
(co-supervisor: Sebastian Ewert, Spotify)
Francisco Rodríguez-Algarra
(completed June 2020) 		A Critical Look at the Music Classification Experiment Pipeline: Using Interventions to Detect and Account for Confounding Effects
(co-supervisor: Bob Sturm, KTH)
Jiajie Dai
(completed March 2019) 		Modelling Intonation and Interaction in Vocal Ensembles
Adib Mehrabi
(completed April 2018) 		Vocal Imitation for Query by Vocalisation
Maria Panteli
(completed April 2018) 		Computational Analysis of World Music Corpora
(co-supervisor: Matthias Mauch)
Zulfadhli Mohamad
(completed April 2018) 		Estimating Performance Parameters from Electric Guitar Recordings
(co-supervisor: Chris Harte)
Siying Wang
(completed Nov 2017) 		Computational Methods for the Alignment and Score-Informed Transcription of Piano Music
(co-supervisor: Sebastian Ewert)
Siddharth Sigtia
(completed Feb 2017) 		Neural Networks for Analysing Music and Environmental Audio
Tian Cheng
(completed Nov 2016) 		Exploiting Piano Acoustics in Automatic Transcription
(co-supervisor: Matthias Mauch)
Magdalena Chudy
(completed Sept 2016) 		Discriminating music performers by timbre: On the relation between instrumental gesture, tone quality and perception in classical cello performance
Robert Tubb
(completed May 2016) 		Creativity, Exploration and Control in Musical Parameter Spaces
Shengchen Li
(completed Mar 2016) 		Expressive Timing Analysis in Classical Piano Performance by Mathematical Model Selection (supervised with Mark Plumbley)
Yading Song
(completed Jan 2016) 		The Role of Emotion and Context in Music Preference
Peter Foster
(completed Apr 2015) 		Information-Theoretic Measures of Predictability for Music Content Analysis
(co-supervisor: Anssi Klapuri)
Holger Kirchhoff
(completed May 2014) 		A User-Assisted Approach to Multiple Instrument Music Transcription
(co-supervisor: Anssi Klapuri)
Amélie Anglade
(completed Apr 2014) 		Logic-based Modelling of Musical Harmony for Automatic Characterisation and Classification
Lesley Mearns
(completed May 2013) 		The Computational Analysis of Harmony in Western Art Music
Emmanouil Benetos
(completed Dec 2012) 		Automatic Transcription of Polyphonic Music Exploiting Temporal Evolution
Robert Macrae
(completed Mar 2012) 		Linking Music Metadata
Matthias Mauch
(completed Mar 2010) 		Automatic Chord Transcription from Audio using Computational Models of Musical Context

Former Research Assistants, Students and Visitors

Ivan Shanin
(Research Assistant on the JazzDAP (Jazz Digital Archive Project) project (Oct 2022 - Aug 2023). 		New Directions in Digital Jazz Studies: Music Information Retrieval and AI Support for Jazz Scholarship in Digital Archives
Keitaro Tanaka
Visiting PhD student (Mar 2023 - Sep 2023) 		Disentangled Representation Learning
Ken O'Hanlon
Postdoctoral Research Assistant on Innovate UK Project in collaboration with Breathe Music Ltd (Nov 2019 - Jun 2021) 		Development of Next-Generation Music Recognition Algorithm for Content Monitoring
Polina Proutskova
(Postdoctoral RA, Dec 2017 - Sep 2019) 		Dig that Lick: Analysing large-scale data for melodic patterns in jazz performances
Wenming Gui
(Visiting Fellow, Oct 2018 - Oct 2019) 		Deep Learning and Singing Voice Detection
Jordan Smith
(Postdoctoral RA, Mar - May 2019) 		Dig that Lick: Analysing large-scale data for melodic patterns in jazz performances
Eita Nakamura
(Visiting Postdoctoral Fellow, Nov 2016 - Oct 2017) 		Note Value Recognition for Rhythm Transcription
Lasse Vetter
(Research student, co-supervised with George Fazekas) 		Polytimbral Instrument Activity Detection using Deep Recurrent Neural Networks
Peter Foster
(Postdoctoral Research Assistant, Nov 2015 - Oct 2016) 		Automatic Transcription of Music (with DoReMIR Music Research AB)
Bruno Di Giorgi
(Visiting PhD Student, Apr - Jul 2016) 		Modelling the Complexity of Tonal Chord Sequences
Matthias Mauch
(Royal Academy of Engineering Research Fellow, 2012-2015) 		Software Systems for Computer-Aided Music Understanding
Emilia Gomez
(Visiting Researcher, Jun - Sep 2015) 		Intonation in Flamenco Singing
Julien Osmalskyj
(Visiting PhD Student, Feb - Jun 2015) 		Cover Song Detection
Peter Foster
(RA Nov 2014 - Aug 2015) 		Audio Data Exploration (with Audio Analytic Ltd)
Siddharth Sigtia
(RA Nov 2014 - Aug 2015) 		Audio Data Exploration (with Audio Analytic Ltd) and Smart Microphone v2.0 (with Audio Analytic Ltd)
Gabrielle Medeot
(Visiting Research Student, Nov 2014 - Apr 2015) 		Memory-enhanced RNN-NADE networks for modelling polyphonic musical sequences
Christof Weiss
(Visiting PhD Student, Feb, Nov 2014) 		A musicologically motivated approach to automatic classification of music data
Lucas Thompson
(Vacation bursary Jun - Aug 2013) 		Analysis of Intonation in Unaccompanied Singing
Alo Allik
(RA Oct 2012 - May 2013) 		A Shared Open Vocabulary for Audio Research and Retrieval
Stephen Welburn
(RA Dec 2011 - Feb 2013) 		Sustainable Management of Digital Music Research Data (2011-12) and Sound Data Management Training (2012-13)
Joachim Ganseman
(Visiting PhD Student, November 2011 - September 2012) 		Sinusoidal modeling based on score-to-audio alignment
Magdalena Chudy
(RA Oct 2011 - Mar 2013) 		MIReS: Roadmap for Music Information ReSearch
Marco Fabiani
(RA October 2011 - May 2012) 		Sustainable Management of Digital Music Research Data
Adam Stark
(RA Dec 2011 - Mar 2012) 		Musicology for the Masses
Xue Wen
(RA Dec 2011 - Mar 2012) 		Musicology for the Masses
Dan Stowell
(RA Sept 2010 - March 2012) 		Musicology for the Masses
Mathieu Barthet
(RA Sept 2010 - Nov 2011) 		Musicology for the Masses
Ivan Damnjanovic
(RA Oct-Nov 2011) 		Sustainable Management of Digital Music Research Data
Asma Rafiq
(Research student) 		Modeling Users' Intentions for the Enhancement of Music Recommendation Systems
Barry Norton
(RA April-July 2011) 		Linked Music Metadata
Thomas Gängler
(RA July 2011) 		Linked Music Metadata
Cedric Mesnage
(RA March-July 2011) 		Linked Music Metadata
Kurt Jacobson
(Research Assistant, 2010) 		Linked Music Metadata

Downloads

Beat tracking software BeatRoot (requires: Java, any platform)
BeatRoot is also available as a VAMP plugin for Sonic Visualiser.

Audio alignment software MATCH (requires: Java, any platform)
MATCH is also available as a VAMP plugin for Sonic Visualiser. There is a tutorial here .

Slides from the ISMIR 2015 Tutorial: Why Singing is Interesting by Simon Dixon, Masataka Goto and Matthias Mauch.

Slides from the IMA 2012 Tutorial on Music Signal Processing, by Mark Plumbley and Simon Dixon.

Slides from the ISMIR 2006 Tutorial on Computational Rhythm Description, by Fabien Gouyon and Simon Dixon.

Teaching

This year I am teaching (with Emmanouil Benetos):

  • ECS7006: Music Informatics (for the MSc in Sound and Music Computing and the PhD programme in Artificial Intelligence and Music).
    • This module introduces students to state-of-the-art methods for the analysis of music data, with a focus on music audio. It presents in-depth studies of general approaches to the low-level analysis of audio signals, and follows these with specialised methods for the high-level analysis of music signals, including the extraction of information related to the rhythm, melody, harmony, form and instrumentation of recorded music. This is followed by an examination of the most important methods of extracting high-level musical content, sound source separation, and on analysing multimodal music data.

I have previously taught the following modules (or parts thereof):
  • Artificial Intelligence
  • Music Analysis and Synthesis
  • Software Tools for Engineers
  • Introduction to Multimedia
  • Knowledge Representation and Reasoning
  • Computational Logic
  • Digital Audio and Computer Music
  • Data Structures and Algorithms
  • Cognitive Science
  • Computer Programming

Biography

I completed my BSc(Hons) (1986-1989) and PhD (1990-1994) degrees in Computer Science at the University of Sydney, and also learnt Classical Guitar at the NSW Conservatorium of Music, obtaining the AMusA (1987) and LMusA (1988). I was a lecturer in Computer Science at Flinders University of South Australia from 1994 until mid 1999, and a research scientist in the Intelligent Music Processing Group at the Austrian Research Institute for Artificial Intelligence from 1999 to 2006. In December 2006 I joined QMUL's Centre for Digital Music as a Lecturer (now Professor), where I am now Deputy Director and lead the Music Informatics theme. I am Director of the UKRI Centre for Doctoral Training in Artificial Intelligence and Music, and founding editor of the journal Transactions of the International Society for Music Information Retrieval. I was Programme Co-chair for the 8th International Conference on Music Information Retrieval (2007) and the 14th International Society for Music Information Retrieval Conference (2013), and General Co-chair for the Dagstuhl Seminar on Multimodal Music Processing (2011) and the 9th International Symposium on Computer Music Modeling and Retrieval (CMMR 2012): Music and Emotions. I was President of the International Society for Music Information Retrieval (2014-15); and am on the Editorial Board of the Journal of New Music Research, and the Advisory Board of the Music Information Retrieval Evaluation Exchange (MIREX).

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