Effect of Listener Experience on Pitch and Rhythm Perception with Tonal Sequences Sandra J. Guzman1, Cody Elston1, Valeriy Shafiro2 & Stanley Sheft2 1Audio Arts & Acoustics, Columbia College, Chicago IL; 2Communication Disorders & Sciences, Rush University, Chicago IL Introduction Experience and training can affect auditory performance, with a general finding that experience interacts with task complexity. Complexity often involves processing of multidimensional stimuli. The current work examined how experience affected dimensional interaction in the processing of tonal sequences defined by both pitch contour and sequence rhythm. Past work has shown varying degrees of relationship between pitch and rhythm perception (e.g., Palmer and Krumhansl, 1987; Peretz and Kolinsky, 1993; Bigand, 1997), with most studies using longer-duration stimuli corresponding to musical phrases. The current work investigated the relationship with relatively brief four-tone sequences. To vary the extent of musical training, subjects were recruited from both music and audio-arts academic programs. Unlike most past work, subjects were grouped for analysis based on task performance rather than a criterion level of musical training. Results Data were first submitted to cluster analysis to group subjects based on sequence-task performance. Performance in all conditions significantly contributed to the analysis. For the two resulting clusters, 8 of the 10 audio-arts students were assigned to group 1, and 6 of the 8 music majors to group 2 (Fig. 2). Audio-arts students and music majors differed significantly (p≤.006) in all metrics of musical training (Fig. 3, left). Despite segregating largely by academic program, between-group differences in musical training were reduced, rather than enhanced, following the cluster analysis which maximized group differences in sequence-task performance (Fig. 3, right). Correlation analysis indicated significant association between cluster group assignment and academic program, but not to any metric of musical training (Table 1, top row). Clearly, collinearity exists among academic program and the training metrics. The semipartial r2 from a multiple linear regression of these variables on cluster results shows the proportion of variance in group assignment uniquely accounted for by each variable. The semipartial r2 for academic program indicated unique account of 17% of variance in cluster group assignment (Table 1, bottom row). For each of the three training metrics, the semipartial r2 was low to negligible. Sequence-task performance in each condition is shown in Fig. 4 for the two cluster groups. Significant between-group differences were obtained in all conditions (p≤.001), with each group significantly better in the Pitch Only than Rhythm Only condition(p≤.01). A split-plot ANOVA indicated a significant interaction between group and condition [F(4,64)=2.99, p=.025]. The basis of the interaction was a difference in the joint processing of pitch and rhythm information. For group 1, the introduction of extraneous rhythm randomization in the Pitch – Rhythm condition led to a significant performance decrement relative the Pitch Only (p=.009) and Pitch & Rhythm (p=.001) conditions. For group 2, these contrasts were not significant. Fig. 1. Illustration of the sequence-reconstruction task. The sequence tones represented by the four boxes labeled A, B, C and D are rearranged in the upper place holders to reconstruct the original or target pattern. Method Subjects: 18 normal-hearing individuals (age range: 19 – 34 yrs; mean: 24.0); 10 were from the Audio Arts program at Columbia College and 8 were music majors. Both majors include auditory training in their curriculum. For Audio Arts (involving sound design and production), training is in both subjective (e.g., sound quality) and objective (e.g., loudness and distortion) critical listening. Music majors are trained in aural skills focusing on melodic dictation, and interval and chord identification. Level of Musical Training: for each subject, training was quantified with three metrics, number of years of instrumental or vocal practice, years of formal lessons, and current hours per week of practice. Pattern-Reconstruction Task: with four-tone frequency patterns, the listening task was to re-assemble the constituent tones in the order of a target sequence (Fig. 1). To increase memory demands, sequence tones were assigned a random response button on each trial. Subjects heard the target sequence only once, but could listen to both constituent tones and their interim reconstruction of the sequence as often as wanted. Correct-answer feedback for each sequence tone was provided after every trial. In each condition, data were collected from a single 25-trial block which was preceded by four practice trials. Stimulus level was 75 dB SPL. Conditions: Identical Target and Response Sequences Pitch Only: fixed tone duration (212 ms) with frequency randomly selected from a logarithmically scaled distribution (400-1750 Hz). Rhythm Only: fixed tone frequency (837 Hz) with a randomly selected log scaled duration (75-600 ms). Pitch & Rhythm: random frequency and duration. Dissimilar Target and Response Sequences Pitch – Rhythm: both frequency and duration were randomized with only frequency defining the target sequence so that the task was reconstructing a pitch contour using a random rhythmic sequence. Rhythm - Pitch: both frequency and duration were randomized with only rhythm defining the target sequence (i.e., rhythm reconstruction with a random pitch sequence). With randomization, a minimum frequency-separation factor of 1.2 and duration-separation factor of 1.4 was assured between any two sequence tones. Fig. 2. Scatter plot of individual performance averaged across the two conditions with only pitch cues (abscissa) and the two with rhythmic cues only (ordinate). Cluster membership is indicated by symbol color. X’s show the two music students assigned to group 1 and the two audio-arts students assigned to group 2. Fig. 4. Box plots showing results from the five conditions in terms of the average number of sequence components correctly placed per trial. The line through each box is the median with the dotted line indicating group average. The dashed line towards the bottom of the figure shows chance performance. Discussion & Summary There were two main findings of this study. 1) Participants could be clustered into two groups based on task performance. Despite collinearity among metrics assessing listener characteristics, academic program, rather than any counting metric of musical training, was the best single predictor of cluster assignment. Thus, various aspects of musical experience and ability were not captured by counting metrics of musical training. The degree to which this observation can be extended to others with a greater extent of musical training and ability than in the current subject cohort is not known. 2) With groups defined by skill level on the current task, a significant interaction between group and sequence-task condition suggests a difference in the manner of integration of pitch and rhythm information. Specifically, the group which performed more poorly showed greater integration across dimensions leading to deleterious effects of extraneous rhythm randomization, while the better-performing group processed the information as if from separable dimensions. Guzman et al. (2014) demonstrated minimal integration in the sequence-reconstruction task with audio-arts students using a protocol in which response buttons were systematically ordered to reduce working-memory load (Fig. 5). The similarity of the pattern of results for the two groups in Fig. 5 suggests that the better-performing listeners of the current study may have benefited from enhanced working memory in the processing of the target tonal sequences. References Bigand E. (1997). J Exp Psych Human Percept Perf 23, 808-822. Guzman S.J., Almeida R., Glass K., et al. (2014). J Acoust Soc Am 135, 2161. Palmer C., & Krumhansl C.L. (1987). J Exp Psych Human Percept Perf 13, 113-126. Peretz I., & Kolinsky R. (1993). Q J Exp Psych 46A, 301-325. Fig. 3. Box plots for level of musical training of subjects in terms of practice and lessons in years, and current hours/week of practice. The line through each box is the median with the dotted line indicating group average. Subjects were grouped according to academic program for the plots on the left, and by cluster group assignment for the plots on the right. Fig. 5. Mean performance in the five sequence-reconstruction conditions. Current results from group 2 are shown with green bars, and the purple bars are for data from a previous study (Guzman et al., 2014) with fixed response-button ordering and audio-arts students as subjects. Error bars represent the 95% confidence intervals. The dashed line shows chance performance. Academic Program Practice (yrs) Lessons (yrs) Current Practice (hrs/week) Pearson r Semipartial r2 .55* .17 .28 .02 .35 >.001 .33 .003 Table 1. Associations between cluster group assignment and level of musical training. In each cell, the top value is the Pearson r, and the bottom value, from a multiple linear regression, is the semipartial r2, indicating the proportion of variance in group assignment uniquely accounted for by the specific dependent variable.