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Clasificación de géneros musicales mediante técnicas de aprendizaje automático
Published in university of Seville bachelor thesis, 2018
Music genre classification using machine learning techniques
Recommended citation: Perez, Miguel & Sarmiento Vega, María Auxiliadora & Fondón García, Irene (2018). " Clasificación de géneros musicales mediante técnicas de aprendizaje automático " Bachelor Thesis, Universtiy of Seville. https://hdl.handle.net/11441/85556
Harmonic Compatibility for Loops in Electronic Music
Published in Pompeu Fabra University master thesis, 2020
Comparison of different techniques methods to asses the compatibility of different electronic music loops
Recommended citation: Perez, Miguel & Ramires, António & Correya, Albin & Font, Frederic (2020). " Harmonic Compatibility for Loops in Electronic Music " master thesis, Universitat Pompeu Fabra. https://zenodo.org/records/4091438
A Comparison of Pitch Chroma Extraction Algorithms
Published in Proceedings of the 19th Sound and Music Computing Conference, 2022
A paper in which we compare qualitative the behaviour of different chroma algorithms, be these based on deep learning or signal processing techniques.
Recommended citation: Perez, Miguel & Kirchhoff, Holger & Serra, Xavier (2022) "A Comparison of Pitch Chroma Extraction Algorithms " Proceedings of the 19th Sound and Music Computing Conference, Saint-Étienne (France). https://zenodo.org/records/6573083
TriAD: Capturing harmonics with 3D convolutions
Published in Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023
In this paper we present a novel architecture capable of capturing the harmonic series using 3D convolutions
Recommended citation: Perez, Miguel & Kirchhoff, Holger & Serra, Xavier (2023). "TriAD: Capturing harmonics with 3D convolutions." Proceedings of the 24th Int. Society for Music Information Retrieval Conference, Milan (Italy). http://ismir2023program.ismir.net/poster_11.html
Improving singing voice transcription generalization with AI-generated accompaniments
Published in Proceedings of the 31st Conference of Multimedia Modeling, 2025
Data augmentation for singing voice-related tasks with music-realistic scenarios through AI-generated music accompaniments.
Recommended citation: Perez, Miguel & Kirchhoff, Holger & Grosche, Peter & Serra, Xavier (2025) "Improving singing voice transcription generalization with AI-generated accompaniments " Proceedings of the 31st conference of Multimedia Modeling, Nara (Japan). https://link.springer.com/chapter/10.1007/978-981-96-2061-6_9
Singing Voice Accompaniment Data Augmentation with Generative Models
Published in 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, 2025
Data augmentation for singing voice-related tasks with music-realistic scenarios through AI-generated music accompaniments.
Recommended citation: Perez, Miguel & Kirchhoff, Holger & Grosche, Peter & Serra, Xavier (2025) "Singing Voice Accompaniment Data Augmentation with Generative Models" 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Hyderabad, India, 2025, pp. 1-5. https://ieeexplore.ieee.org/document/11011167
Refining audio-to-score alignment for singing voice transcription
Published in Proceedings of the 22nd Sound and Music Computing Conference, 2025
Audio-to-score alignment based on iterative alignment of discrete events
Recommended citation: Perez, Miguel & Kirchhoff, Holger & Grosche, Peter & Serra, Xavier (2025) "Refining audio-to-score alignment for singing voice transcription" Proceedings of the 22nd Sound and Music Computing Conference, Graz (Austria). https://zenodo.org/records/15838731