The purpose of this study was to examine the relationships among beat perception, error detection, and musical experience. We presented monophonic rhythms using a piano timbre along with two measures of beat perception (Harvard Beat Finding and Interval Test [BFIT] and Goldsmiths Beat Alignment Test) and a measure of melodic error detection. College musicians’ (N = 43) ability to detect rhythm errors was not significantly correlated to their ability to perceive beat alignment (Goldsmiths test) or tempo change (BFIT). Age was related to performance on only one of the measures, the BFIT test. A regression model yielded pitch error detection as the only significant predictor of rhythmic error detection. We suggest that college musicians already possess a requisite ability for beat processing that allows them to perform error detection. The lack of relationship between beat perception and rhythmic error detection is explained by this requisite ability in the population, and we promote future research for pitch and rhythm processing as it relates to rhythm perception or performance.
AllenM. J.YenW. M. (2001). Introduction to measurement theory. Waveland Press.
2.
BakerD. J.VenturaJ.CalamiaM.ShanahanD.ElliottE. M. (2020). Examining musical sophistication: A replication and theoretical commentary on the Goldsmiths Musical Sophistication Index. Musicae Scientiae, 24(4), 411–429. https://doi.org/10.1177/1029864918811879
3.
BouwerF. L.BurgoyneJ. A.OdijkD.HoningH.GrahnJ. A. (2016). What makes a rhythm complex? The influence of musical training and accent type on beat perception. PLoS ONE, 13(1), Article e0190322. https://doi.org/10.1371/journal.pone.0190322
4.
BouwerF. L.BurgoyneJ. A.OdijkD.HoningH.GrahnJ. A. (2018). What makes a rhythm complex? The influence of musical training and accent type on beat perception. PLoS ONE, 13(1), 1–26.
5.
BrandM.BurnsedV. (1981). Music abilities and experiences as predictors of error-detection skill. Journal of Research in Music Education, 29(2), 91–96. https://doi.org/10.2307/3345017
6.
BuonviriN. O. (2019). Effects of silence, sound, and singing on melodic dictation accuracy. Journal of Research in Music Education, 66, 365–374. https://doi.org/10.1177/0022429418801333
7.
ByoJ. L. (1992). Effects of barlines, pitch, and meter on musicians’ rhythm reading performance. Journal of Band Research, 27(2), 34–44.
8.
ByoJ. L. (1993). The influence of textural and timbral factors on the ability of music majors to detect performance errors. Journal of Research in Music Education, 41(2), 156–167. https://doi.org/10.2307/3345405
9.
ByoJ. L. (1997). The effects of texture and number of parts on the ability of music majors to detect performance errors. Journal of Research in Music Education, 45(1), 51–66. https://doi.org/10.2307/3345465
10.
CavittM. E. (2003). A descriptive analysis of error correction in instrumental music rehearsals. Journal of Research in Music Education, 51(3), 218–230. https://doi.org/10.1016/B978-012672690-9/50010-X
11.
ClarkT.WilliamonA. (2011). Imagining the music: Methods for assessing musical imagery ability. Psychology of Music, 40(4), 471–493. https://doi.org/10.1177/0305735611401126
12.
CoxA. (2016). Music and embodied cognition: Listening, moving, feeling, and thinking. Indiana University Press.
13.
DavisS. (2010). Error detection in the aural skills class: Research and pedagogy. Journal of Music Theory Pedagogy, 24, 37–67.
14.
DeCarboN. (1984). The effect of years of teaching experience and major performance instrument on error detection scores of instrumental music teachers. Contributions to Music Education, 11, 28–32.
15.
DrakeC.GrosL.PenelA. (1999). How fast is that music? The relation between physical and perceived tempo. In YiS. W. (Ed.), Music, mind, and science (pp. 190–203). Seoul National University.
16.
DukeR. A.GeringerJ. M.MadsenC. K. (1991). Performance of perceived beat in relation to age and music training. Journal of Research in Music Education, 39(1), 35–45. https://doi.org/10.2307/3344607
17.
FarleyA. L. P. (2014). The relationship between musicians’ internal pulse and rhythmic sight-reading [Unpublished doctoral dissertation]. University of Washington.
18.
ForsytheJ. L.WoodsJ. R. (1983). The effects of conducting on the error detection ability of undergraduate and graduate instrumental conductors. Contributions to Music Education, 10, 27–32. https://doi.org/10.2307/24127375
19.
FujiiS.SchlaugG. (2013). The Harvard Beat Assessment Test (H-BAT): A battery for assessing beat perception and production and their dissociation. Frontiers in Human Neuroscience, 7, Article 771. https://doi.org/10.3389/fnhum.2013.00771
20.
GonzoC. L. (1971). An analysis of factors related to choral teachers’ ability to detect pitch errors while reading the score. Journal of Research in Music Education, 19(3), 259–271. https://doi.org/10.2307/3343762
21.
GroulxT. (2013). The influence of tonal and atonal contexts on error detection accuracy. Journal of Research in Music Education, 61(2), 233–243. https://doi.org/10.1177/0022429413485602
22.
GrunowR. F. (1980). An investigation of the relative effectiveness of four modes of score preparation on visual-aural discrimination skills development [Unpublished dissertation]. University of Michigan.
23.
HenryM. J.HerrmannB. (2014). Low-frequency neural oscillations support dynamic attending in temporal context. Timing and Time Perception, 2(1), 62–86. https://doi.org/10.1163/22134468-00002011
24.
JonesM. R. (1976). Time our lost dimension: Toward a new theory of perception, attention, and memory. Psychological Review, 83(5), 323–355. https://doi.org/10.1037/0033-295x.83.5.323
25.
KillianJ. (1991). The relationship between sightsinging accuracy and error detection in junior high singers. Journal of Research in Music Education, 39(3), 216–224. https://doi.org/10.2307/3344721
26.
KuhnT. L. (1974). Discrimination of modulated beat tempo by professional musicians. Journal of Research in Music Education, 22(4), 270–277. https://doi.org/10.2307/3344892
27.
KungH.-N. (2017). Cultural influence on the perception and cognition of musical pulse and meter [Unpublished doctoral dissertation]. The Ohio State University.
28.
LarsonR. C. (1997). Relationships between melodic error detection, melodic dictation, and melodic sightsinging. Journal of Research in Music Education, 25(4), 264–271. https://doi.org/10.2307/3345267
29.
LondonJ. (2011). Tactus ≠ tempo: Some dissociations between attentional focus, motor behavior, and tempo judgment. Empirical Musicology Review, 6(1), 43–55. https://doi.org/10.18061/1811/49761
30.
MatthewsT. E.ThibodeauJ. N. L.GuntherB. P.PenhuneV. B. (2016). The impact of instrument-specific musical training on rhythm perception and production. Frontiers in Psychology, 7, Article 69. https://doi.org/10.3389/fpsyg.2016.00069
MikszaP.ElpusK. (2018). Design and analysis for quantitative research in music education. Oxford University Press.
33.
MishraJ. (2016). Rhythmic and melodic sight reading interventions: Two meta-analyses. Psychology of Music, 44(5), 1082–1094. https://doi.org/10.1177/0305735615610925
34.
MüllensiefenD.GingrasB.MusilJ.StewartL. (2014). The musicality of non-musicians: An index for assessing musical sophistication in the general population. PLoS ONE, 9(2), Article e89642. https://doi.org/10.1371/journal.pone.0089642
35.
MüllensiefenD.GingrasB.StewartL.MusilJ. J. (2013). Goldsmiths Musical Sophistication Index (Gold-MSI) v1.0 technical report and documentation revision 0.3. Technical Report. https://www.gold.ac.uk/music-mind-brain/gold-msi/
36.
NápolesJ.BabbS.BowersJ.HankleS.ZrustA. (2017). The effect of piano playing on preservice teachers’ ability to detect errors in a choral score. Journal of Music Teacher Education, 26(2), 149–162. https://doi.org/10.1177/1057083716639724
37.
NicholsB. E.SpringerD. G. (2021). Interval identification predicts success in melodic dictation. Journal of Research in Music Education. Advance online publication. https://doi.org/10.1177/00224294211011962
38.
NicholsB. E.WöllnerC.HalpernA. (2018). Score one for jazz: Working memory in jazz and classical musicians. Psychomusicology: Music, Mind, and Brain, 28(2), 101–107. https://doi.org/10.1037/pmu0000211
39.
PotterD. D.FenwickM.AbecasisD.BrochardR. (2009). Perceiving rhythm where none exists: Event-related potential (ERP) correlates of subjective accenting. Cortex, 45(1), 103–109. https://doi.org/10.1016/j.cortex.2008.01.004
40.
PovelD.-J.EssensP. J. (1985). Perception of temporal patterns. Music Perception, 2(4), 411–440. https://doi.org/10.2307/40285311
41.
RussellC. R. (2019). Effects of pitch and rhythm priming tasks on accuracy and fluency during sight-reading. Journal of Research in Music Education, 67(3), 252–269. https://doi.org/10.1177/0022429419851112
42.
SchlegelA. (2010). The effect of directed attention score study procedures on music majors’ error detection in three-part instrumental music [Doctoral dissertation, Louisiana State University]. https://digitalcommons.lsu.edu/gradschool_dissertations/1215
43.
ShawT. (1971). A program to improve choral conducting students’ ability to detect rhythmic errors in choral rehearsal. Dissertation Abstracts International, 32(12), 7034A.
44.
SheldonD. (2004). Effects of multiple listenings on error-detection acuity in multivoice, multitimbral musical examples. Journal of Research in Music Education, 52(2), 102–115. https://doi.org/10.2307/3345433
45.
StambaughL. (2016). Differences in error detection skills by band and choral preservice teachers. Journal of Research in Music Education, 25(2), 25–36. https://doi.org/10.1177/1057083714558421
46.
StambaughL.NicholsB. E. (2020). The relationships among interval identification, pitch error detection, and stimulus timbre by preservice teachers. Journal of Research in Music Education, 67(4), 465–480. https://doi.org/10.1177/0022429419885931
47.
TabachnickB. G.FidellL. S. (2007). Using multivariate statistics. Pearson.
48.
TaylorC. C. (1963). Critique of a study of the ability of musicians to detect melodic and harmonic errors in the performance of choral music while inspecting the score. Bulletin of the Council for Research in Music Education, 1(1), 45–49.
49.
ThompsonW. F.SchellenbergE. G. (2002). Cognition constraints on music listening. In ColwellR.RichardsonC. (Eds.), The new handbook of research on music teaching and learning (pp. 461–468). Oxford University Press.
50.
ThorntonL. C. (2008). The effect of grade, experience, and listening condition on the melodic error detection of fifth- and sixth-grade woodwind students. Update: Applications of Research in Music Education, 26(2), 4–10. https://doi.org/10.1177/8755123308317612
51.
van NoordenL.MoelantsD. (1999). Resonance in the perception of musical pulse. Journal of New Music Research, 28(1), 43–66. https://doi.org/10.1076/jnmr.28.1.43.3122
52.
WilliamsM. (2021). The effect of focus of attention on error detection ability. Journal of Research in Music Education. Advance online publication. http://doi.org/10.1177/0022429421997449
53.
WöllnerC.HalpernA. (2016). Attentional flexibility and memory capacity in conductors and pianists. Attention, Perception, & Psychophysics, 78, 198–208. https://doi.org/10.3758/s13414-015-0989-z
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