Abstract-In this paper we propose a rhythmically-informed method for onset detection in polyphonic music. Music is highly structured in terms of the temporal regularity underlying onset occurrences and this rhythmic structure can be used to locate sound events. Using a probabilistic formulation, the method integrates information extracted from the audio signal and rhythmic knowledge derived from tempo estimates in order to exploit the temporal expectations associated with rhythm and make musically meaningful event detections. To do so, the system explicitly models note events in terms of the elapsed time between consecutive events and decodes the most likely sequence of onsets that led to the observed audio signal. In this way, the proposed method is able to identify likely time instants for onsets and to successfully exploit the temporal regularity of music. The goal of this work is to define a general framework to be used in combination with any onset detection function and tempo estimator. The method is evaluated using a dataset of music that contains multiple instruments playing at the same time, including singing and different music genres. Results show that the use of rhythmic information improves the commonly used adaptive thresholding onset detection method which only considers local information. It is also shown that the proposed probabilistic framework successfully exploits rhythmic information using different detection functions and tempo estimation algorithms.
In this paper we explore the relationship between the temporal and rhythmic structure of musical audio signals. Using automatically extracted rhythmic structure we present a rhythmically-aware method to combine note onset detection techniques. Our method uses topdown knowledge of repetitions of musical events to improve detection performance by modelling the temporal distribution of onset locations. Results on a publicly available database demonstrate that using musical knowledge in this way can lead to significant improvements by reducing the number of missed and spurious detections.
The use of sonification for navigation, localization and obstacle avoidance is considered to be one of the most important tasks in auditory display research for its potential application to navigation systems in vehicles and smartphones, assistive technology and other eyes-free applications. The aim of this technology is to deliver location-based information to support navigation through sound. In this paper a comparison of two sonification methods for navigation and obstacle avoidance is presented. These methods were initially developed during a sonification hack day that was ran during the Interactive Sonification (ISon) workshop 2013. In order to allow the formal comparison of methods, we followed a reproducible sonification approach using a set of guidelines provided by SonEX (Sonification Evaluation eXchange). SonEX is a community-based environment that enables the definition and evaluation of standardized tasks, supporting open science standards and reproducible research. In order to allow for reproducible research, the system has been made publicly available
Abstract-We present a new evaluation method for measuring the performance of musical audio beat tracking systems. Central to our method is a novel visualisation, the beat error histogram, which illustrates the metrical relationship between two qausiperiodic sequences of time instants: the output of beat tracking system and a set of ground truth annotations. To quantify beat tracking performance we derive an information theoretic statistic from the histogram. Results indicate that our method is able to measure performance with greater precision than existing evaluation methods and implicitly cater for metrical ambiguity in tapping sequences.
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