Mirex-2010 “audio Beat Tracking” Task: Ircambeat Submission

This extended abstract details a submission to the Music Information Retrieval Evaluation eXchange (MIREX) 2010 for the “Audio Beat Tracking” task. The system named ircambeat performs time-variable tempo and meter estimation, beat and downbeat marking. Detailed description of the various parts can be found in [1], [2] and [3]. We briefly summarized them below. 1. IRCAMBEAT IMPLEMENTATION The last version of Ircambeat is currently only available as Matlab pcode. Previous versions are available as C++ executable or library running under Linux, Windows-XP and Mac-OS-X. The last version performs time-variable tempo and meter estimation, beat and downbeat marking. 2. IRCAMBEAT ALGORITHM DESCRIPTION The flowchart of ircambeat is represented in Figure 1. 2.1 Tempo and meter estimation The tempo and meter estimation algorithm works in three stages. First, an onset-energy-function f(t) is extracted from the audio signal by computing a reassigned spectral-energyflux (using time and frequency reassignement for better precision). Second, the dominant periodicities of f(t) over time are estimated using a combination of Discrete Fourier Transform and Frequency-Mapped Auto-Correlation-Function. The combination of both allows to better emphasizing the periodicities due to the meter, the beat and the tatum periodicities in f(t). We note p(t) the resulting function. Finally, a Viterbi decoding algorithm is used to decode simultaneously the tempo and the meter. For this, we define states of a hidden Markov model as all the combinations of possible tempi and meter (among 22: binary grouping of beat/ binary subdivision of beat, 23: binary/ ternary and 32: ternary/ binary). Given p(t), we compute the observation probabilities of the states over time. The Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. c © 2010 International Society for Music Information Retrieval. Figure 1. Flowchart of ircambeat decoding then produces the best estimates of tempo and meter over time. More details about the algorithm can be found in [1]. 2.2 Beat and downbeat tracking Beat and downbeat positions are estimated simultaneously using an inverse Viterbi formulation. In this formulation, a state is defined as a specific time. Observation probabilities of states (times) are obtained using a LDA-trained beat-template. This beat-template is obtained by considering the function f(t) inside a measure as a N-dimensional feature vector. A two-class (beat/ non-beat) problem is then solved using LDA and a training set. The resulting LDA-axe is then used as the best beat-template in order to perform discrimination between beat and non-beat positions. More details about the beat estimation algorithm can be found in [2] and [3]. Downbeat estimation is described in [3]. 3. MIREX-2010 RESULTS AND DISCUSSIONS