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An Overview on Networked Music Performance Technologies
Open accessAbstract
Networked music performance (NMP) is a potential game changer among Internet applications, as it aims at revolutionizing the traditional concept of musical interaction by enabling remote musicians to interact and perform together through a telecommunication network. Ensuring realistic performance conditions, however, constitutes a significant engineering challenge due to the extremely strict requirements in terms of network delay and audio quality, which are needed to maintain a stable tempo, a satisfying synchronicity between performers and, more generally, a high-quality interaction experience. In this paper, we offer a review of the psycho-perceptual studies conducted in the past decade, aimed at identifying latency tolerance thresholds for synchronous real-time musical performance. We also provide an overview of hardware/software enabling technologies for NMP, with a particular emphasis on system architecture paradigms, networking configurations, and applications to real use cases.
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Cited by
Turchet, L., West, T., & Wanderley, M. M. (2021) · Personal and Ubiquitous Computing · doi:10.1007/s00779-020-01395-2 · Cited by 104
Smart Musical Instruments: Vision, Design Principles, and Future Directions
Turchet, L. (2019) · IEEE Access · doi:10.1109/access.2018.2876891 · Cited by 94
“, wireless sensor networks [23]), networked music performance systems [92], sensors and actuator augmentations typical of augmented instruments [72], and embedded intelligence tailored to support real-time audio and sensor processing.”
Background
Metadata
- Authors
- Rottondi, C., Chafe, C., Allocchio, C., & Sarti, A.
- Venue
- IEEE Access
- Published
- 2016
- Volume
- 4
- Pages
- 8823-8843
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2560180317
- Cited by
- 203
- References
- 0
- FWCI
- 5.93
- Type
- journal article
- Language
- en
- Open access
- gold
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- Rottondi, C., Chafe, C., Allocchio, C., & Sarti, A. (2016). An Overview on Networked Music Performance Technologies. IEEE Access. https://doi.org/10.1109/access.2016.2628440
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.