From live framedrum performance to music notation: a data-driven approach

Vryzas N, Bountourakis V, Pagonis A. From live framedrum performance to music notation: a data-driven approach. In: Express Paper. Audio Engineering Society; 2024. Paper 246. Available from: https://aes.org/publications/elibrary-page/?id=22592

@inproceedings{Vryzas2024_22592,
  author = {Vryzas, Nikolaos and Bountourakis, Vasileios and Pagonis, Antonis},
  title = {{From live framedrum performance to music notation: a data-driven approach}},
  note = {Paper 246},
  year = {2024},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22592}
}

TY  - CPAPER
TI  - From live framedrum performance to music notation: a data-driven approach
AU  - Vryzas, Nikolaos
AU  - Bountourakis, Vasileios
AU  - Pagonis, Antonis
M1  - Paper 246
PY  - 2024
DA  - 2024/06/06
UR  - https://aes.org/publications/elibrary-page/?id=22592
PB  - Audio Engineering Society
LA  - en
AB  - This research focuses on utilizing the traditional frame drum as an input sensor for the creation of music sheets without the need for manual transcription, by training and evaluating models on a dataset containing samples from various frame drums and playing techniques. The existing dataset is extended to include recordings from different frame drums with varying attributes and playing techniques for improved generalization. CNN-based models are employed for audio sample recognition between the main hitting techniques and playing positions. Additional modules for pitch recognition and onset detection are proposed in the system architecture. The models are trained and evaluated on individually recorded samples.
ER  -