All Outputs (6)

Building an Embodied Musicking Dataset for co-creative music-making (2024)
Conference Proceeding
Vear, C., Poltronieri, F., Didonato, B., Zhang, Y., Benerradi, J., Hutchinson, S., …Malekmohamadi, H. (in press). Building an Embodied Musicking Dataset for co-creative music-making. In Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-56992-0_24

In this paper, we present our findings of the design, development and deployment of a proof-of-concept dataset that captures some of the physiological, musicological, and psychological aspects of embodied musicking. After outlining the conceptual ele... Read More about Building an Embodied Musicking Dataset for co-creative music-making.

Evaluation of digital musicianship in higher education through playing and creating digital scores (2024)
Conference Proceeding
Moroz, S., Vear, C., & Poltronieri, F. (2024). Evaluation of digital musicianship in higher education through playing and creating digital scores. In Tenor Zurich 2024 (18-28)

This paper presents an evaluation of digital musicianship with digital scores. Primary data was gathered during the DigiScore “Roadshow”of North American universities’ music departments in 2023 and an extended research workshop in Avellino, Italy, 20... Read More about Evaluation of digital musicianship in higher education through playing and creating digital scores.

Generating emotional music based on improved C-RNN-GAN (2024)
Conference Proceeding
Shi, X., & Vear, C. (2024). Generating emotional music based on improved C-RNN-GAN. In Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-56992-0_23

This study introduces an emotion-based music generation model built upon the foundation of C-RNN-GAN, incorporating conditional GAN, and utilizing emotion labels to create diverse emotional music. Two evaluation methods were employed in this study to... Read More about Generating emotional music based on improved C-RNN-GAN.

Jess+: AI and Robotics with Inclusive Music-Making (2024)
Conference Proceeding
Vear, C., Hazzard, A., Moroz, S., & Benerradi, J. (in press). Jess+: AI and Robotics with Inclusive Music-Making. . https://doi.org/10.1145/3613904.3642548

This paper discusses the findings from a cross-sector research project investigating how a digital score created using AI and robotics might stimulate new creative opportunities and relationships within the practices of an inclusive music ensemble. T... Read More about Jess+: AI and Robotics with Inclusive Music-Making.

Human-AI Musicking: A Framework for Designing AI for Music Co-creativity (2023)
Conference Proceeding
Vear, C., Benford, S., Avila, J. M., & Moroz, S. (2023). Human-AI Musicking: A Framework for Designing AI for Music Co-creativity.

In this paper, we present a framework for understanding human-AI musicking. This framework prompts a series of questions for reflecting on various aspects of the creative interrelationships between musicians and AI and thus can be used as a tool for... Read More about Human-AI Musicking: A Framework for Designing AI for Music Co-creativity.

Five Provocations for a More Creative TAS (2023)
Conference Proceeding
Benford, S., Hazzard, A., Vear, C., Webb, H., Chamberlain, A., Greenhalgh, C., …Marshall, J. (2023). Five Provocations for a More Creative TAS. In TAS ‘23: Proceedings of The First International Symposium on Trustworthy Autonomous Systems 11-12 July 2023 Edinburgh, UK. https://doi.org/10.1145/3597512.3599709

Conventional wisdom has it that trustworthy autonomous systems (AS) should be explainable, dependable, controllable and safe tools for humans to use. Reflecting on a portfolio of artistic applications of TAS leads us adopt an alternative stance and t... Read More about Five Provocations for a More Creative TAS.