Search Results for author: Pedro Sarmento

Found 8 papers, 3 papers with code

The GigaMIDI Dataset with Features for Expressive Music Performance Detection

1 code implementation24 Feb 2025 Keon Ju Maverick Lee, Jeff Ens, Sara Adkins, Pedro Sarmento, Mathieu Barthet, Philippe Pasquier

This curated iteration of GigaMIDI encompasses expressively-performed instrument tracks detected by NOMML, containing all General MIDI instruments, constituting 31% of the GigaMIDI dataset, totalling 1, 655, 649 tracks.

Information Retrieval Music Information Retrieval

MIDI-to-Tab: Guitar Tablature Inference via Masked Language Modeling

no code implementations9 Aug 2024 Drew Edwards, Xavier Riley, Pedro Sarmento, Simon Dixon

Guitar tablatures enrich the structure of traditional music notation by assigning each note to a string and fret of a guitar in a particular tuning, indicating precisely where to play the note on the instrument.

Decoder Language Modeling +2

ProgGP: From GuitarPro Tablature Neural Generation To Progressive Metal Production

no code implementations11 Jul 2023 Jackson Loth, Pedro Sarmento, CJ Carr, Zack Zukowski, Mathieu Barthet

Recent work in the field of symbolic music generation has shown value in using a tokenization based on the GuitarPro format, a symbolic representation supporting guitar expressive attributes, as an input and output representation.

Music Generation

From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generation

no code implementations18 Apr 2023 Adarsh Kumar, Pedro Sarmento

Subword tokenization has been widely successful in text-based natural language processing (NLP) tasks with Transformer-based models.

Music Generation

DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models

1 code implementation30 Jul 2021 Pedro Sarmento, Adarsh Kumar, CJ Carr, Zack Zukowski, Mathieu Barthet, Yi-Hsuan Yang

In this work, we present DadaGP, a new symbolic music dataset comprising 26, 181 song scores in the GuitarPro format covering 739 musical genres, along with an accompanying tokenized format well-suited for generative sequence models such as the Transformer.

Decoder Genre classification +3

Determination of spectroscopic parameters for 313 M dwarf stars from their APOGEE Data Release 16 H-band spectra

1 code implementation8 Mar 2021 Pedro Sarmento, Bárbara Rojas-Ayala, Elisa Delgado Mena, Sergi Blanco-Cuaresma

The scientific community's interest on the stellar parameters of M dwarfs has been increasing over the last few years, with potential applications ranging from galactic characterization to exoplanet detection.

Solar and Stellar Astrophysics

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