M. McCallum, M. E. P. Davies, F. Henkel, J. Kim, and S. E. Sandberg, On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations. In Proc. of ICASSP, Seoul, South Korea, April, 2024
[arxiv]
M. McCallum, F. Henkel, J. Kim, S. E. Sandberg, and M. E. P. Davies, Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search. In Proc. of ICASSP, Seoul, South Korea, April, 2024
[arxiv]
F. Henkel, J. Kim, M. McCallum, S. E. Sandberg, and M. E. P. Davies, Tempo estimation as fully self-supervised binary classification. In Proc. of ICASSP, Seoul, South Korea, April, 2024
[arxiv]
C. -Y. Chiu, M. Müller, M. E. P. Davies, A. W. -Y. Su and Y. -H. Yang, Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 31, pp. 2824-2835, 2023
[arxiv] [doi] [Code]
G. Morais, M. E. P. Davies, M. Queiroz and M. Fuentes, Tempo vs. Pitch: Understanding Self-Supervised Tempo Estimation. In Proc. of ICASSP, Rhodes Island, Greece, pp. 1-5, March, 2023
[arxiv] [doi] [Code]
C. -Y. Chiu, M. Müller, M. E. P. Davies, A. W. -Y. Su and Y. -H. Yang, An Analysis Method for Metric-Level Switching in Beat Tracking. IEEE Signal Processing Letters, 29, pp. 2153-2157, 2022
[arxiv] [doi] [Code]
S. Sulun, M. E. P. Davies, and P. Viana, Symbolic music generation conditioned on continuous-valued emotions. IEEE Access, 10, pp. 44617-44626, 2022 (Open Access)
[doi] [Supplementary Material] [Code]
M. E. P. Davies, S. Böck, and M. Fuentes, Tempo Beat and Downbeat Estimation. ISMIR 2021 Tutorial, (online) 2021
[url]
J. Fonseca, M. Fuentes, F. Bonini Baraldi, and M. E. P. Davies, On the use of automatic onset detection for the analysis of Maracatu de Baque Solto. In Correia Castilho, L., Dias, R., Pinho, J.F. (eds) Perspectives on Music, Sound and Musicology. Current Research in Systematic Musicology, vol 10. Springer, ChamIn Perspectives on Music, Sound, and Musicology: Research, Education and Practice, pp 209–225, 2021
[doi]
A. Sá Pinto, S. Böck, J. S. Cardoso, and M. E. P. Davies, User-Driven Fine-Tuning for Beat Tracking. Electronics, Special Issue in Machine Learning Applied to Music/Audio Signal Processing, 10(13), 1518, 2021 (Open Access)
[doi]
A. Sá Pinto, and M. E. P. Davies, Tapping Along to the Difficult Ones: Leveraging User-Input for Beat Tracking in Highly Expressive Musical Content. In Perception, Representations, Image, Sound, Music: 14th International Symposium, CMMR 2019, Marseille, France, October 14–18, 2019, Revised Selected Papers, Springer International Publishing, Lecture Notes in Computer Science, Volume 12631, pp 75-90, 2021
[doi]
S. Sulun and M. E. P. Davies, On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks. IEEE Journal of Selected Topics in Signal Processing, 15(1), pp. 132-142, 2021
[doi] [Supplementary Material]
M. E. P. Davies, M. Fuentes, J. Fonseca, L. Aly, M. Jerónimo, and F. Bonini Baraldi, Moving in Time: Computational Analysis of Microtiming in Maracatu de Baque Solto. Proc. of the 21st Int. Society for Music Information Retrieval Conf., Montréal, Canada, pp. 795-802, October, 2020
[Link to paper, poster, and video]
S. Böck and M. E. P. Davies, Deconstruct, Analyse, Reconstruct: How to improve Tempo, Beat, and Downbeat Estimation. Proc. of the 21st Int. Society for Music Information Retrieval Conf., Montréal, Canada, pp. 574-582, October, 2020. Winner of Best Evaluation Award
[Link to paper, poster, and video] [Supplementary Material]
A. Sá Pinto, I. Domingues, and M. E. P. Davies, Shift If You Can: Counting and Visualising Correction Operations for Beat Tracking Evaluation. In Extended Abstracts for the Late-Breaking Demo Session of the 21st Int. Society for Music Information Retrieval Conf., Montréal, Canada, October, 2020
[Link] [Code]
A. Ramires, G. Bernardes, M. E. P. Davies, and X. Serra, TIV.lib: an open-source library for the tonal description of musical audio. In Proc. of the 23rd Intl. Conference on Digital Audio Effects (DAFx2020), Vienna, Austria (online), pp. 304-309, September 2020
[Paper] [Video] [Code]
O. Nieto, M. McCallum, M. E. P. Davies, A. Robertson, A. Stark, and E. Egozy, The Harmonix Set: Beats, Downbeats, And Functional Segment Annotations Of Western Popular Music. In Proc. of ISMIR 2019, Delft, Netherlands, pp. 565-572, November 2019
[Paper] [Dataset]
S. Böck, M. E. P. Davies, and P. Knees, Multi-task Learning of Tempo and Beat: Learning One to Improve the Other. In Proc. of ISMIR 2019, Delft, Netherlands, pp. 486-493, November, 2019
[Paper] [Supplementary Material]
A. Sá Pinto and M. E. P. Davies, Towards user-informed beat tracking of musical audio. In Proc. of CMMR 2019, Marseille, France, pp. 577-588, October, 2019
[Proceedings link]
M. E. P. Davies and S. Böck, Temporal Convolutional Networks for Musical Audio Beat Tracking. In Proc. of EUSIPCO 2019, A Coruña, Spain, September, 2019
[doi]
P. López-Serrano, M. E. P. Davies, J. Hockman, C. Dittmar, and M. Müller, Break-informed Audio Decomposition For Interactive Redrumming. In Late-Breaking Demo Session of ISMIR 2018, Paris, France, September 2018
[Abstract] [Supplementary Material]
M. Miron and M. E. P. Davies, High frequency magnitude spectrogram reconstruction for music mixtures using convolutional autoencoders. In Proc. of the 21st Intl. Conference on Digital Audio Effects (DAFx-18), Aveiro, Portugal, pp. 173-180, September 2018
[Paper] [Supplementary Material]
G. Sioros, M. E. P. Davies, and C. Guedes, A generative model for the characterization of musical rhythms. Journal of New Music Research, 47(2), pp. 114-128, 2018
[doi]
G. Bernardes, M. E. P. Davies, and C. Guedes, A Hierarchical Harmonic Music Mixing Method. In Music Technology with Swing: 13th International Symposium, CMMR 2017, Matosinhos, Portugal, September 25-28, 2017, Revised Selected Papers, Springer International Publishing, Lecture Notes in Computer Science, Volume 11265, pp 151-170, 2018
[doi]
M. Aramaki, M. E. P. Davies, R. Kronland-Martinet, and S. Ystad, Music Technology with Swing: 13th International Symposium, CMMR 2017, Matosinhos, Portugal, September 25-28, 2017, Revised Selected Papers. Springer International Publishing, Lecture Notes in Computer Science, Volume 11265, 2018
[doi]
C. Jin, M. E. P. Davies, and P. Campisi, Embedded Systems Feel the Beat in New Orleans: Highlights from the IEEE Signal Processing Cup 2017 Student Competition. IEEE Signal Processing Magazine, 34(4), pp. 143-170, July 2017 (Open Access)
[doi]
A. Ramires, R. Penha and M. E. P. Davies, User Specific Adaptation in Automatic Transcription of Vocalised Percussion. In Proc. of RecPad-2017, Amadora, Portugal, pp. 19-20, October, 2017
[Proceedings link]
A. Ramires, D. Cocharro and M. E. P. Davies, An audio-only method for advertisement detection in broadcast television content. In Proc. of RecPad-2017, Amadora, Portugal, pp. 21-22, October, 2017
[Proceedings link]
G. Bernardes, M. E. P. Davies, and C. Guedes, A Perceptually-Motivated Harmonic Compatibility Method for Music Mixing. In Proc. of CMMR 2017, Matosinhos, Portugal, pp. 104-115, October, 2017
[Paper]
G. Bernardes, M. E. P. Davies, and C. Guedes, Automatic Musical Key Estimation with Adaptive Mode Bias. In Proc. of ICASSP 2017, New Orleans, USA, pp. 316-320, March, 2017
[doi]
G. Bernardes, D. Cocharro, C. Guedes and M. E. P. Davies, Harmony Generation Driven by a Perceptually Motivated Tonal Interval Space. ACM Computers in Entertainment, Special Issue on Musical Metacreation, Part I, 14(2), Article No. 6, 2016
[doi]
G. Bernardes, D. Cocharro, M. Caetano, C. Guedes and M. E. P. Davies, A Multi-Level Tonal Interval Space for Modelling Pitch Relatedness and Musical Dissonance. Journal of New Music Research, 45, pp. 281-294, 2016
[doi]
R. Gebhardt, M. E. P. Davies and B. U. Seeber, Psychoacoustic Approaches for Harmonic Music Mixing. Applied Sciences, Special Issue in Audio Signal Processing, 6(5), 123, 2016 (Open Access)
[doi]
G. Bernardes, D. Cocharro, C. Guedes, M. E. P. Davies, Conchord: An Application for Generating Musical Harmony by Navigating in the Tonal Interval Space. In Music, Mind, and Embodiment: 11th International Symposium, CMMR 2015, Plymouth, UK, June 16-19, 2015, Revised Selected Papers, Springer International Publishing, Lecture Notes in Computer Science, Volume 9617, pp 243-260, 2016
[doi]
A. Sá Pinto, M. E. P. Davies, and P. Herrera, Semantic Modelling for User Interaction with Sonic Content. In Proc. of RecPad-2016, Aveiro, Portugal, pp. 91-93, October, 2016
[Proceedings link]
G. Bernardes, L. Aly, and M. E. P. Davies, SEED: Resynthesizing Environmental Sounds from Examples. In Proc. of Sound and Music Computing Conference (SMC-2016), Hamburg, Germany, pp. 55-62, September, 2016
[Proceedings link]
B. Dias, D. M. Matos, M. E. P. Davies, and H. S. Pinto, Time Stretching & Pitch Shifting with the Web Audio API: Where are we at?. In Proc. of Web Audio Conference (WAC-2016), Atlanta, USA, April, 2016
[Paper]