# Impact of Audio Delay and Quality in Network Music Performance +
## 7 Conclusions and Future Work  
This paper presents the results from a controlled NMP experiment with 11 pairs of musicians (22 musicians in total), where we varied either the audio delay or the audio quality between the participants and measured multiple quality of experience variables via questionnaires. The musicians played different instruments in different musical genres. To the best of our knowledge, this was the largest NMP study where actual musicians played real musical pieces and the analysis was performed with multi-faceted questionnaires. The questionnaires completed by the participants indicate that even though growing delays between the musicians affect their quality of experience, the tolerance level of musicians to delay can be higher than what has previously been reported by studies relying on synchronized hand clapping. While there is no abrupt threshold, we found that one-way (M2E) delays of 40 ms still yielded a positive QoE for many participants. The participants in our NMP study found that their performances were synchronized and satisfactory even when the one-way (M2E) delay reached 40 ms. This indicates that the Ensemble Performance Threshold (EPT) for NMP is at least 40 ms, for a wide range of instruments and musical pieces, rather than the 25-30 ms previously cited in the literature, which was based on hand-clapping studies. This supports our initial hypothesis H1, rejecting N1. We also found that reducing audio quality did not affect the quality of experience of the musicians, even when the sampling rate dropped from 88.2 kHz to 8 kHz, an order of magnitude decrease in bitrate. However, certain subsets of participants (notably pianists) were more sensitive to these changes, suggesting that recommended sampling rates may need to account for timbral detail and instrument type. This implies that when the available bandwidth for an NMP session is limited, or when low-latency CPU processing is a priority, we can save bandwidth by reducing the audio sampling rate, with no appreciable loss in QoE and without introducing an audio compression/decompression algorithm that would impose additional delay. This supports our initial hypothesis H2, rejecting N2. We have also analyzed the audio files recorded during our variable delay experiments, using signal processing techniques, in order to detect the musician's tempo, observe how it changes throughout each session and compare it with the actual delay used [34]. We verified that musicians slow down their tempo when delay grows, something observed in many previous studies. In addition, we found that most musicians could synchronize and maintain a stable tempo when the delay was up to 40 ms but not when it grew to 60 ms. This strengthens the results of the QoE analysis in this paper (hypothesis H1),i.e., that the delay threshold for NMP when actual musical pieces are performed, is closer to 40 ms. As the 40 ms EPT is very close to what we have measured that a commercial 5G Non-Standalone network can provide in real-world conditions [4], we expect that as 5G Standalone networks are deployed, offering improved and more predictable latencies, mobile NMP will become a reality. As future work, exploring the relationship between the instrument, style and tempo and the QoE is an obvious direction; we already saw that pianists and their partners were more influenced by delay in this study, an observation that we attribute to their lengthier and more formal training. However, this analysis requires performing a much larger number of experiments in order to allow for statistically significant results. Ideally, our setup will be duplicated by other research groups, adding more observations to our data set. We are also analyzing the videos recorded during our experiments with machine learning-based emotion recognition tools, which first recognize facial features and then translate them into emotions.