With the zeitgeist of economic globalization and the rapid development of broadband internet infrastructure, human communications have embraced the virtual realm. From banking, stocks, news, to food, rides, and now education, more and more aspects of information exchange happen online rather than in person. In the domain of music, however, though post-production and distribution are happening more often online, with talent collaboration platforms such as ‘fiverr’ and streaming services such as Spotify and YouTube, live networked performances from distributed musicians have yet to be embraced by the mainstream. This paper outlines the challenges faced by both the technicians and the musicians when attempting to play music through a network. Important research that attempts to work around these obstacles has been summarized.
The idea of networked music is simple. Like the concept of the telephone that enables people in different locations to talk to each other in ‘real-time’, networked music attempts to enable musicians in different locations to play music together, “without all the bother of buying plane tickets and the time it takes to travel (Oliveros, 2009, p. 433).” The economic advantages for such a way of music-making are straightforward and its applications all-encompassing, from distributed recording sessions to mobile music gaming, to online karaoke rooms. In a traditional performative sense, the audience of a networked performance can experience multicultural performances within their own context at the same time (Backman, 2011). However, the reality of these visions at a technological level still faces inevitable obstacles that make music performance as we understand in real life almost impossible to execute over a network.
The main reason for this is network latency. Because of the time it takes for a signal to travel through various network protocols and geopolitical barriers, a typical roundtrip latency for a long-distance voice call is around 200ms (Backman, 2011). In the past two decades, various attempts at reducing this latency have been made in commercial and academic realms alike. Since its creation in 2007 at CCRMA, Stanford University, JackTrip has been extensively used as the software for transmitting high-quality audio with low latency for network music performances within high-speed research networks. Yet the ‘Mouth to Ear’ latency can seldomly be reduced to the minimum requirement for group ensemble performance, which is within 24ms (Gurevish et al., 2004; Bartlette et al., 2006; Hupke et al., 2019; Tsioutas et al., 2019). As a result, many research endeavors have been conducted to find creative solutions to such a limitation.
Technically, besides creating software like JackTrip to reduce latency, numerous attempts have been made to enhance synchronization between distributed musicians. In Renaud’s research (2011, p.1), “a semi-standardized cueing framework” for networks with over 50ms of latency had been proposed. Subsequently, Alexandrak and Bader proposed a scheme of utilizing computer accompaniment techniques, triggering pre-recorded solos to represent remote musicians in real time (2014). Recently, progress has been made in creating a ‘global metronome’ to accurately account for latencies across distributed musicians (Hupke et al., 2019). This method utilizes two distributed metronomes and GPS positioning to determine the latency between participants. It then adds artificial latency between the network to realize a ‘delayed’ ensemble synchronization between musicians.
From the perspective of musicians, frameworks of Quality of Service (QoS) and Quality of Experience (QoE) of Networked Music Performance have been proposed (Colmenares et al., 2013; Tsioutas et al., 2019). In Tsioutas et al.’s research, a new measurement concept “Quality of Musician’s Experience (QoME) that combines subjective and objective measures of a networked session is being proposed. These measurements include variables ranging from room acoustics, performer’s affective states, classification of the music being played, as well as network latency, audio quality, and network jitter into account forming a holistic picture of the experience. Interestingly, in a small scale educational setting, Iorwerth et al.’s case studies of remote music performance learning done between The University of the Highlands and Islands and Glasgow Caledonian University have shown that network latency is not the most troublesome factor affecting negatively towards QoE, but rather, time management and communication turn out to be more challenging online.
In conclusion, networked music performance is a fast-growing research topic. It will likely be referenced in a wide range of applications, not limited to stage performance. As most recent research concludes, the quality and direction of future research in Networked Performance will greatly depend on technological developments with latency reduction being the end goal. There may be one day where ultra-low latency communication (within the minimum requirement for ensemble synchronization) can be achieved. In the meantime, more attention will be paid on improving the overall Quality of Experience for these applications on the individual level, as well as on effectively creating specific genres to maximize the potency of spectatorship of such events.
Citations
Alexandrak, C., & Bader, R. (2014, January). Using computer accompaniment to assist networked music performance. In Audio Engineering Society Conference: 53rd International Conference: Semantic Audio. Audio Engineering Society.
Backman, J. (2011, September). Portable and Networked Devices for Musical Creativity. In Audio Engineering Society Conference: 43rd International Conference: Audio for Wirelessly Networked Personal Devices. Audio Engineering Society.
Bartlette, C., Headlam, D., Bocko, M., & Velikic, G. (2006). Effect of network latency on interactive musical performance. Music Perception: An Interdisciplinary Journal, 24(1), 49-62.
Colmenares, J. A., Peters, N., Eads, G., Saxton, I., Jacquez, I., Kubiatowicz, J. D., & Wessel, D. (2013). A multicore operating system with QoS guarantees for network audio applications. Journal of the Audio Engineering Society, 61(4), 174-184.
Gurevish, M., Chafe, C., Leslie, G., & Tyan, S. (2004, November). Simulation of Networked Ensemble Performance with Varying Time Delays: Characterization of Ensemble Accuracy. In ICMC.
Hupke, R., Beyer, L., Nophut, M., Preihs, S., & Peissig, J. (2019, October). Effect of a Global Metronome on Ensemble Accuracy in Networked Music Performance. In Audio Engineering Society Convention 147. Audio Engineering Society.
Hupke, R., Sridhar, S., Genovese, A., Nophut, M., Preihs, S., Beyer, T., ... & Peissig, J. (2019, October). A Latency Measurement Method for Networked Music Performances. In Audio Engineering Society Convention 147. Audio Engineering Society.
Iorwerth, M., Moore, D., & Knox, D. (2015, August). Challenges of using Networked Music Performance in education. In Audio Engineering Society Conference: UK 26th Conference: Audio Education. Audio Engineering Society.
Oliveros, P. (2009). Networked Music: Low and High Tech. Contemporary Music Review, 28(4-5), 433-435.
Oliveros, P., Weaver, S., Dresser, M., Pitcher, J., Braasch, J., & Chafe, C. (2009). Telematic music: six perspectives. Leonardo Music Journal, 19(1), 95-96.
Renaud, A. B. (2011, November). Cueing and composing for long distance network music collaborations. In Audio Engineering Society Conference: 44th International Conference: Audio Networking. Audio Engineering Society.
Tsioutas, K., Doumanis, I., & Xylomenos, G. (2019, March). A framework for understanding and defining Quality of Musicians’ Experience in Network Music Performance environments. In Audio Engineering Society Convention 146. Audio Engineering Society.