Effect of Leadership Change on Microtiming Patterns in String Quartet

aBirmingham City University, Sound and Music Analysis (SoMA) Group, Birmingham, UK
bUniversity of Birmingham, Birmingham, UK

Abstract

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.

Leadership and Performance Styles

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:

    — Deadpan (DP) performances with minimal expression in tempo and articulation
    — Normal (NR) concert style performances
    — Speed (SP) performances with a spontaneous accelerando and decelerando initiated by the leader once in each performance

Dataset

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:

    — 72 performances, total of 288 individual recordings

Microtiming Patterns of String Quartet Musicians

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.

Microtiming pattern visualisation example.

Figure 1: Microtiming pattern visualisation example for the cello playing Haydn’s Op. 74 Finale.

    — Note onsets are shown as yellow dots
    — Onsets include pitch and metrical subdivision labels
    — Four eighth-notes in a bar are quantised to the annotated downbeat locations
    — Metrical grid covers bars 1-48 in 2/4 metre
    — Vertical dashed blue lines represent means and standard deviation values
    — Histograms of onset locations are shown at the bottom
    — Means are shown as percentages for each subdivision in an isochronous metrical grid with values 0%, 25%, 50% and 100%

Microtiming Results

    — The experiment compares two leadership changes in three performance styles (NR, DP and SP).
    — Means of microtiming pattern deviations in % are shown per instrument (in colour) for each performance style with additional per-performance style means and per-instrument means shown above and below plots, respectively.
    — The experiment investigates microtiming patterns for onsets quantised to the annotated downbeat positions.
    — All individual results in the following sections use downbeat annotations from the corresponding leader.

First violinist as leader - Deadpan

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.

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First violin

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Second violin

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Viola

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Cello


First violinist as leader - Normal

Per instrument microtiming patterns for performances 1 to 12 in normal style.

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First violin

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Second violin

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Viola

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Cello


First violinist as leader - Speed

Per instrument microtiming patterns for performances 1 to 12 in speed style.

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First violin

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Second violin

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Viola

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Cello


Second violinist as leader - Deadpan

Per instrument microtiming patterns for performances 1 to 12 in deadpan style.

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First violin

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Second violin

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Viola

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Cello


Second violinist as leader - Normal

Per instrument microtiming patterns for performances 1 to 12 in normal style.

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First violin

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Second violin

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Viola

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Cello


Second violinist as leader - Speed

Per instrument microtiming patterns for performances 1 to 12 in speed style.

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First violin

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Second violin

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Viola

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Cello

Microtiming patterns for annotated downbeat locations.

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.

Microtiming pattern results RPPW 2023.

Conclusions

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.

References

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).

BibTeX

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}
}