Dataset Information

From beat tracking to beat expectation: Cognitive-based beat tracking for capturing pulse clarity through time.

ABSTRACT: Pulse is the base timing to which western music is commonly notated, generally expressed by a listener by performing periodic taps with their hand or foot. This cognitive construction helps organize the perception of timed events in music and is the most basic expectation in rhythms. The analysis of expectations, and more specifically the strength with which the beat is felt-the pulse clarity-has been used to analyze affect in music. Most computational models of pulse clarity, and rhythmic expectation in general, analyze the input as a whole, without exhibiting changes through a rhythmic passage. We present Tactus Hypothesis Tracker (THT), a model of pulse clarity over time intended for symbolic rhythmic stimuli. The model was developed based on ideas of beat tracking models that extract beat times from musical stimuli. Our model also produces possible beat interpretations for the rhythm, a fitness score for each interpretation and how these evolve in time. We evaluated the model's pulse clarity by contrasting against tapping variability of human annotators achieving results comparable to a state-of-the-art pulse clarity model. We also analyzed the clarity metric dynamics on synthetic data that introduced changes in the beat, showing that our model presented doubt in the pulse estimation process and adapted accordingly to beat changes. Finally, we assessed if the beat tracking generated by the model was correct regarding listeners tapping data. We compared our beat tracking results with previous beat tracking models. The THT model beat tracking output showed generally correct estimations in phase but exhibits a bias towards a musically correct subdivision of the beat.

SUBMITTER: Miguel MA

PROVIDER: S-EPMC7673539 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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From beat tracking to beat expectation: Cognitive-based beat tracking for capturing pulse clarity through time.

Miguel Martin Alejandro MA Sigman Mariano M Fernandez Slezak Diego D

PloS one 20201118 11

Pulse is the base timing to which western music is commonly notated, generally expressed by a listener by performing periodic taps with their hand or foot. This cognitive construction helps organize the perception of timed events in music and is the most basic expectation in rhythms. The analysis of expectations, and more specifically the strength with which the beat is felt-the pulse clarity-has been used to analyze affect in music. Most computational models of pulse clarity, and rhythmic expec ...[more]

PMID: 33206697

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Project description:Single Particle Tracking (SPT) is a well known class of tools for studying the dynamics of biological macromolecules moving inside living cells. In this paper, we focus on the problem of localization and parameter estimation given a sequence of segmented images. In the standard paradigm, the location of the emitter inside each frame of a sequence of camera images is estimated using, for example, Gaussian fitting (GF), and these locations are linked to provide an estimate of the trajectory. Trajectories are then analyzed by using Mean Square Displacement (MSD) or Maximum Likelihood Estimation (MLE) techniques to determine motion parameters such as diffusion coefficients. However, the problems of localization and parameter estimation are clearly coupled. Motivated by this, we have created an Expectation Maximization (EM) based framework for simultaneous localization and parameter estimation. We demonstrate this framework through two representative methods, namely, Sequential Monte Carlo combined with Expectation Maximization (SMC-EM) and Unscented Kalman Filter combined with Expectation Maximization (U-EM). Using diffusion in two-dimensions as a prototypical example, we conduct quantitative investigations on localization and parameter estimation performance across a wide range of signal to background ratios and diffusion coefficients and compare our methods to the standard techniques based on GF-MSD/MLE. To demonstrate the flexibility of the EM based framework, we do comparisons using two different camera models, an ideal camera with Poisson distributed shot noise but no readout noise, and a camera with both shot noise and the pixel-dependent readout noise that is common to scientific complementary metal-oxide semiconductor (sCMOS) camera. Our results indicate our EM based methods outperform the standard techniques, especially at low signal levels. While U-EM and SMC-EM have similar accuracy, U-EM is significantly more computationally efficient, though the use of the Unscented Kalman Filter limits U-EM to lower diffusion rates.

Dataset Information

From beat tracking to beat expectation: Cognitive-based beat tracking for capturing pulse clarity through time.

Publications

From beat tracking to beat expectation: Cognitive-based beat tracking for capturing pulse clarity through time.

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