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This paper describes a newly-launched public evaluation challenge on acoustic scene classification and detection of sound events within a scene. Systems dealing with such tasks are far from exhibiting human-like performance and robustness. Undermining factors are numerous: the extreme variability of sources of interest possibly interfering, the presence of(More)
An increasing number of researchers work in computational auditory scene analysis (CASA). However, a set of tasks, each with a well-defined evaluation framework and commonly used datasets do not yet exist. Thus, it is difficult for results and algorithms to be compared fairly, which hinders research on the field. In this paper we will introduce a(More)
This paper addresses the problem of tracking partials, i.e., determining the evolution over time of the parameters of a given number of sinusoids with respect to the analyzed audio stream. We first show that the minimal frequency difference heuristic generally used to identify continuities between local maxima of successive short-time spectra can be(More)
The predominant melodic source, frequently the singing voice, is an important component of musical signals. In this paper, we describe a method for extracting the predominant source and corresponding melody from ldquoreal-worldrdquo polyphonic music. The proposed method is inspired by ideas from computational auditory scene analysis. We formulate(More)
Expressing the similarity between musical streams is a challenging task as it involves the understanding of many factors which are most often blended into one information channel: the audio stream. Consequently, separating the musical audio stream into its main melody and its accompaniment may prove as being useful to root the similarity computation on a(More)
This paper introduces a new method for improving the accuracy in medium scale music similarity problems. Recently , it has been shown that the raw accuracy of query by example systems can be enhanced by considering priors about the distribution of its output or the structure of the music collection being considered. The proposed approach focuses on reducing(More)
In this paper, we introduce a new partial tracking method suitable for the sinusoidal modeling of mixtures of instrumental sounds with pseudo-stationary frequencies. This method, based on the linear prediction of the frequency evolutions of the partials, enables us to track these partials more accurately at the analysis stage, even in complex sound(More)
The identification of the instruments playing in a poly-phonic music signal is an important and unsolved problem in Music Information Retrieval. In this paper, we propose a framework for the sound source separation and tim-bre classification of polyphonic, multi-instrumental music signals. The sound source separation method is inspired by ideas from(More)
In this paper, we introduce a new analysis technique particularly suitable for the sinusoidal modeling of non-stationary signals. This method, based on amplitude and frequency modulation estimation , aims at improving traditional Fourier parameters and enables us to introduce a new peak selection process, so that only peaks having coherent parameters are(More)