While determining an appropriate tempo is crucial to music performers, composers and listeners, few empirical studies have investigated the musical factors affecting tempo choices. In two experiments we examined how aspects of musical pitch affect tempo choice, by asking participants (musically trained and untrained) to adjust the tempi of melodic sequences varying in pitch register and pitch direction, as well as sequences typically associated with specific registers in common period music. In Experiment 1, faster tempi were assigned to higher registers. Specific melodic direction (rise vs. fall) did not affect tempo preferences; nevertheless, pitch change in both directions elicited faster tempi than a repeating, unchanging pitch. The effect of register on tempo preference was stronger for participants with music training, and also (unexpectedly) for female participants. In Experiment 2, melodic figures typically related to lower and higher parts in common-period music were associated with slower and faster tempi, respectively. Results support a “holistic” notion of musical tempo, viewing the choice of proper tempo as determined by interactions among diverse musical dimensions, including aspects of pitch structure, rather than by rhythmic considerations alone. The experimental design presented here can be further applied to explore the effects of other musical parameters on tempo preferences.

There is a growing trend to teach playing an instrument such as a piano at home using an automated system. A key component of such systems is the ability to rate performance of the learner in order to provide feedback and select appropriate exercises. In this study, we expand on previous works that have developed automatic evaluation systems for an overall grade by also providing predictions for specific aspects of performance: pitch, rhythm, tempo, and articulation & dynamics, as well as scheduling what is an appropriate next task. We describe how a set of salient features is extracted UMAP '22, July 4-7, 2022, Barcelona, Spain Tamir-Ostrover et al. by comparing MIDI performance data of three piano players to an ideal performance, how the features used for evaluation are selected, and evaluate using linear regression how well the selected features are able to predict the mean scores given by a group of domain experts (piano teachers). Relatively good 𝑅 2 scores (0.54 to 0.68) are achieved using a small number of features (2 -4). Such automatic evaluation of different aspects of performance can be used as a part of an automatic learning system, and to help provide learners with detailed feedback on their performance. CCS CONCEPTS• Human-centered computing → Sound-based input / output; User models.

Zohar Eitan and Hila Tamir-Ostrover start their chapter with a survey of existing empirical studies of sound-space mappings—in particular, pitch/spatial height associations. Using Ligeti’s Endless Column as a case, they exemplify how music might challenge these mappings by pointing out contradictions in the associative link between the auditory dimension and spatial and motion features. These contradictions, the authors argue, on the one hand can illustrate novel opportunities for composers to use music-space correspondences to create paradoxical spaces while, on the other hand, could demonstrate how the music-space correspondence revealed by empirical research could be used in the analysis of music.