This study investigated the effects of changes in leadership on microtiming patterns of different players within a string quartet. By quantising note onset positions within eighth-note metrical structure of bar-length rhythmic patterns, it is possible to extract, visualise and analyse microtiming patterns of each musician over time. The majority of previous studies have focused on microtiming patterns of percussion instruments, and relatively few have explored analysis of string instruments.
In Tomczak et al. (2022), we showed that onset annotations from multiple annotators typically exhibit some variation. To limit the extent of the measurable annotation variation, we manually verify the outputs of automatic onset and downbeat detection methods (Böck et al., 2012; 2016).Here, we examined the synchronisation of musicians to a designated leader (i.e., first or second violinist) in a string quartet using CARAT Python library, a computational approach presented in Rocamora et al. (2019). The stimuli included expert-verified onset and downbeat annotations from 72 performances of Haydn’s Op. 74 No. 1 Finale played in three different performance styles, which totalled 288 individual recordings from the Virtuoso Strings dataset (Tomczak et al., 2022).
Our results revealed reduced microtiming accuracy of each player when new leader’s downbeat annotations were used. Specifically, when the musicians were instructed to follow the second and not the first violinist, they played significantly late on every metrical position. Conversely, in a familiar performance context, their synchronisation to the leader’s timing was more precise for each metrical position under the leadership of the first violinist.
The musicians in the string quartet played in three performance styles under the leadership of the first and the second violinists. The performance styles are:
We use note onset and downbeat annotations for the recordings part of the Virtuoso Strings Dataset.
The musicians in the string quartet played in three performance styles under the leadership of the first and the second violinists. The performance styles are:
Microtiming patterns of four musicians in a quartet can be visualised by quantising note onset positions within an eighth-note metrical structure of bars in a performance. In this study we use Haydn’s Op. 74 No. 1 Finale with the score available here. Each musicians’ annotated note onset positions and downbeat positions are first annotated and then used to visualise microtiming patterns over time.
Figure 1: Microtiming pattern visualisation example for the cello playing Haydn’s Op. 74 Finale.
Per instrument microtiming patterns for performances 1 to 12 in deadpan style. Patterns in the following figures are visualised using annotated downbeats of the designated leader.
First violin
Second violin
Viola
Cello
Per instrument microtiming patterns for performances 1 to 12 in normal style.
First violin
Second violin
Viola
Cello
Per instrument microtiming patterns for performances 1 to 12 in speed style.
First violin
Second violin
Viola
Cello
Per instrument microtiming patterns for performances 1 to 12 in deadpan style.
First violin
Second violin
Viola
Cello
Per instrument microtiming patterns for performances 1 to 12 in normal style.
First violin
Second violin
Viola
Cello
Per instrument microtiming patterns for performances 1 to 12 in speed style.
First violin
Second violin
Viola
Cello
Mean results for two leaderships and three performance styles. Means of microtiming pattern deviations in % are shown per instrument for each performance style. Additional means per instrument and performance style are shown above and below, respectively.
This study investigated the changes in microtiming patterns of musicians in a string quartet after changing the ensemble's leader. Our analysis revealed reduced microtiming accuracy of each player when new leader's downbeat annotations were used. Specifically, when the musicians were instructed to follow the second and not the first violinist, they played significantly late on every metrical position. Conversely, in a familiar performance context, their synchronisation to the leader's timing was more precise for each metrical position under the leadership of the first violinist. The results highlighted that the presented analysis is a promising approach for studying microtiming in string quartet recordings in future work.
Tomczak, M., Li, M.S., Bradbury, A., Elliott, M., Stables, R., Witek, M., Goodman, T., Abdlkarim, D., Di Luca, M., Wing, A. and Hockman, J., 2022. Annotation of Soft Onsets in String Ensemble Recordings. arXiv preprint arXiv:2211.08848.
Böck, S., Krebs, F. and Schedl, M., 2012. Evaluating the Online Capabilities of Onset Detection Methods. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR).
Böck, S., Krebs, F. and Widmer, G., 2016. Joint Beat and Downbeat Tracking with Recurrent Neural Networks. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR).
Rocamora, M., Jure, L., Fuentes, M., Maia, L. and Biscainho, L., 2019. CARAT: Computer-Aided Rhythmic Analysis Toolbox. Late-Breaking Demo (LBD) in the International Society for Music Information Retrieval Conference (ISMIR).
Feel free to cite this abstract:
@article{tomczak2023effect,
title={Effect of Leadership Change on Microtiming Patterns in String Quartet},
author={Tomczak, Maciej and Li, Min Susan and Witek, Maria and Hockman, Jason},
journal={19th Rhythm Perception and Production Workshop},
year={2023}
}