publication . Preprint . 2020

OrchideaSOL: a dataset of extended instrumental techniques for computer-aided orchestration

Cella, Carmine Emanuele; Ghisi, Daniele; Lostanlen, Vincent; Lévy, Fabien; Fineberg, Joshua; Maresz, Yan;
Open Access English
  • Published: 01 Jul 2020
Abstract
This paper introduces OrchideaSOL, a free dataset of samples of extended instrumental playing techniques, designed to be used as default dataset for the Orchidea framework for target-based computer-aided orchestration. OrchideaSOL is a reduced and modified subset of Studio On Line, or SOL for short, a dataset developed at Ircam between 1996 and 1998. We motivate the reasons behind OrchideaSOL and describe the differences between the original SOL and our dataset. We will also show the work done in improving the dynamic ranges of orchestral families and other aspects of the data.
Subjects
free text keywords: Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
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Preprint . 2020
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[1] Y. Maresz, “On computer-assisted orchestration,” Contemporary Music Review, vol. 32, no. 1, pp. 99-109, 2013. [OpenAIRE]

[2] G. Carpentier and J. Bresson, “Interacting with symbol, sound, and feature spaces in orchide´e, a computeraided orchestration environment,” Computer Music Journal, vol. 34, no. 1, pp. 10-27, 2010.

[3] M. Caetano and C.-E. Cella, “Imitative computer-aided musical orchestration with biologically inspired algorithms,” in Handbook of Artificial Intelligence for Music, E. Miranda, Ed. Springer, 2020, to appear.

[4] J. Gillick, C.-E. Cella, and D. Bamman, “Estimating Unobserved Audio Features for Target-Based Orchestration,” in Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019. [OpenAIRE]

[5] G. Ballet, R. Borghesi, P. Hoffmann, and F. Le´vy, “Studio online 3.0: An internet ”killer application” for remote access to ircam sounds and processing tools,” Journe´e dInformatique Musicale (JIM), 1999.

[6] F. Le´vy, “STUDIO ON LINE: Une pre´sentation ge´ne´rale (internal report),” Ircam, Tech. Rep., 1999.

[7] J. Fineberg, “IRCAM Instrumental Data Base (internal report),” Ircam, Tech. Rep., 1996.

[8] C. Steinmetz, “csteinmetz1/pyloudnorm: 0.1.0,” Nov. 2019. [Online]. Available: https://doi.org/10.5281/ zenodo.3551801

[9] D. Bogdanov, N. Wack, E. Go´mez Gutie´rrez, S. Gulati, H. Boyer, O. Mayor, G. Roma Trepat, J. Salamon, J. R. Zapata Gonza´lez, X. Serra et al., “Essentia: An audio analysis library for music information retrieval,” in Proceedings of the 14th Conference of the International Society for Music Information Retrieval (ISMIR), 2013.

[10] V. Lostanlen, J. Ande´n, and M. Lagrange, “Extended playing techniques: The next milestone in musical instrument recognition,” in Proceedings of the International Conference on Digital Libraries for Musicology (DLfM), 2018. [OpenAIRE]

[11] D. Huppenkothen, B. McFee, and L. Nore´n, “Entrofy Your Cohort: A Data Science Approach to Candidate Selection,” arXiv preprint arXiv:1905.03314, 2019. [OpenAIRE]

[12] R. Bittner, M. Fuentes, D. Rubinstein, A. Jansson, K. Choi, and T. Kell, “mirdata: Software for Reproducible Usage of Datasets,” in Proceedings of the International Society on Music Information Retrieval (ISMIR) Conference, 2019. [OpenAIRE]

[13] B. McFee, V. Lostanlen, M. McVicar, A. Metsai, S. Balke, C. Thom, C. Raffel, A. Malek, D. Lee, F. Zalkow, K. Lee, O. Nieto, J. Mason, D. Ellis, R. Yamamoto, S. Seyfarth, E. Battenberg, V. Morozov, R. Bittner, K. Choi, J. Moore, Z. Wei, S. Hidaka, P. Friesch, F.-R. Stter, D. Here, T. Kim, M. Vollrath, and A. Weiss, “librosa/librosa: 0.7.2,” Jan. 2020. [Online]. Available: https://doi.org/10.5281/zenodo. 3606573

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Abstract
This paper introduces OrchideaSOL, a free dataset of samples of extended instrumental playing techniques, designed to be used as default dataset for the Orchidea framework for target-based computer-aided orchestration. OrchideaSOL is a reduced and modified subset of Studio On Line, or SOL for short, a dataset developed at Ircam between 1996 and 1998. We motivate the reasons behind OrchideaSOL and describe the differences between the original SOL and our dataset. We will also show the work done in improving the dynamic ranges of orchestral families and other aspects of the data.
Subjects
free text keywords: Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Related Organizations
Download from
arXiv.org e-Print Archive
Preprint . 2020
Provider: arXiv.org e-Print Archive

[1] Y. Maresz, “On computer-assisted orchestration,” Contemporary Music Review, vol. 32, no. 1, pp. 99-109, 2013. [OpenAIRE]

[2] G. Carpentier and J. Bresson, “Interacting with symbol, sound, and feature spaces in orchide´e, a computeraided orchestration environment,” Computer Music Journal, vol. 34, no. 1, pp. 10-27, 2010.

[3] M. Caetano and C.-E. Cella, “Imitative computer-aided musical orchestration with biologically inspired algorithms,” in Handbook of Artificial Intelligence for Music, E. Miranda, Ed. Springer, 2020, to appear.

[4] J. Gillick, C.-E. Cella, and D. Bamman, “Estimating Unobserved Audio Features for Target-Based Orchestration,” in Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019. [OpenAIRE]

[5] G. Ballet, R. Borghesi, P. Hoffmann, and F. Le´vy, “Studio online 3.0: An internet ”killer application” for remote access to ircam sounds and processing tools,” Journe´e dInformatique Musicale (JIM), 1999.

[6] F. Le´vy, “STUDIO ON LINE: Une pre´sentation ge´ne´rale (internal report),” Ircam, Tech. Rep., 1999.

[7] J. Fineberg, “IRCAM Instrumental Data Base (internal report),” Ircam, Tech. Rep., 1996.

[8] C. Steinmetz, “csteinmetz1/pyloudnorm: 0.1.0,” Nov. 2019. [Online]. Available: https://doi.org/10.5281/ zenodo.3551801

[9] D. Bogdanov, N. Wack, E. Go´mez Gutie´rrez, S. Gulati, H. Boyer, O. Mayor, G. Roma Trepat, J. Salamon, J. R. Zapata Gonza´lez, X. Serra et al., “Essentia: An audio analysis library for music information retrieval,” in Proceedings of the 14th Conference of the International Society for Music Information Retrieval (ISMIR), 2013.

[10] V. Lostanlen, J. Ande´n, and M. Lagrange, “Extended playing techniques: The next milestone in musical instrument recognition,” in Proceedings of the International Conference on Digital Libraries for Musicology (DLfM), 2018. [OpenAIRE]

[11] D. Huppenkothen, B. McFee, and L. Nore´n, “Entrofy Your Cohort: A Data Science Approach to Candidate Selection,” arXiv preprint arXiv:1905.03314, 2019. [OpenAIRE]

[12] R. Bittner, M. Fuentes, D. Rubinstein, A. Jansson, K. Choi, and T. Kell, “mirdata: Software for Reproducible Usage of Datasets,” in Proceedings of the International Society on Music Information Retrieval (ISMIR) Conference, 2019. [OpenAIRE]

[13] B. McFee, V. Lostanlen, M. McVicar, A. Metsai, S. Balke, C. Thom, C. Raffel, A. Malek, D. Lee, F. Zalkow, K. Lee, O. Nieto, J. Mason, D. Ellis, R. Yamamoto, S. Seyfarth, E. Battenberg, V. Morozov, R. Bittner, K. Choi, J. Moore, Z. Wei, S. Hidaka, P. Friesch, F.-R. Stter, D. Here, T. Kim, M. Vollrath, and A. Weiss, “librosa/librosa: 0.7.2,” Jan. 2020. [Online]. Available: https://doi.org/10.5281/zenodo. 3606573

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