'1e0a': A Computational Approach to Rhythm Training

TL;DR

This paper introduces a web-based computational system that assesses and guides rhythm learning by generating increasingly complex patterns and providing feedback based on performance deviations, mimicking a teacher-student interaction.

Contribution

It presents a novel rhythm training system that dynamically adjusts pattern complexity based on perceptual processing metrics, enhancing rhythm learning effectiveness.

Findings

The system accurately assesses learner performance using statistical deviations.

The complexity metric correlates with perceptual processing of rhythmic patterns.

The web-based application improves accessibility for rhythm training.

Abstract

We present a computational assessment system that promotes the learning of basic rhythmic patterns. The system is capable of generating multiple rhythmic patterns with increasing complexity within various cycle lengths. For a generated rhythm pattern the performance assessment of the learner is carried out through the statistical deviations calculated from the onset detection and temporal assessment of a learner's performance. This is compared with the generated pattern, and their performance accuracy forms the feedback to the learner. The system proceeds to generate a new pattern of increased complexity when performance assessment results are within certain error bounds. The system thus mimics a learner-teacher relationship as the learner progresses in their feedback-based learning. The choice of progression within a cycle for each pattern is determined by a predefined complexity metric. This metric is based on a coded element model for the perceptual processing of sequential stimuli. The model earlier proposed for a sequence of tones and non-tones, is now used for onsets and silences. This system is developed into a web-based application and provides accessibility for learning purposes. Analysis of the performance assessments shows that the complexity metric is indicative of the perceptual processing of rhythm patterns and can be used for rhythm learning.