Download Analytical Features for the Classification of Percussive Sounds: The Case of the Pandeiro There is an increasing need for automatically classifying sounds for MIR and interactive music applications. In the context of supervised classification, we describe an approach that improves the performance of the general bag-of-frame scheme without loosing its generality. This method is based on the construction and exploitation of specific audio features, called analytical, as input to classifiers. These features are better, in a sense we define precisely than standard, general features, or even than ad hoc features designed by hand for specific problems. To construct these features, our method explores a very large space of functions, by composing basic operators in syntactically correct ways. These operators are taken from the Mathematical and Audio Processing domains. Our method allows us to build a large number of these features, evaluate and select them automatically for arbitrary audio classification problems. We present here a specific study concerning the analysis of Pandeiro (Brazilian tambourine) sounds. Two problems are considered: the classification of entire sounds, for MIR applications, and the classification of attacks portions of the sound only, for interactive music applications. We evaluate precisely the gain obtained by analytical features on these two problems, in comparison with standard approaches.
Download Sinusoid Modeling in a Harmonic Context This article discusses harmonic sinusoid modeling. Unlike standard sinusoid analyzers, the harmonic sinusoid analyzer keeps close watch on partial harmony from an early stage of modeling, therefore guarantees the harmonic relationship among the sinusoids. The key element in harmonic sinusoid modeling is the harmonic sinusoid particle, which can be found by grouping short-time sinusoids. Instead of tracking short-time sinusoids, the harmonic tracker operates on harmonic particles directly. To express harmonic partial frequencies in a compact and robust form, we have developed an inequality-based representation with adjustable tolerance on frequency errors and inharmonicity, which is used in both the grouping and tracking stages. Frequency and amplitude continuity criteria are considered for tracking purpose. Numerical simulations are performed on simple synthesized signals.
Download Musical Signal Analysis Using Fractional-Delay Inverse Comb Filters A novel filter configuration for the analysis of harmonic musical signals is proposed. The method is based on inverse comb filtering that allows for the extraction of selected harmonic components or the background noise component between the harmonic spectral components. A highly accurate delay required in the inverse comb filter is implemented with a high-order allpass filter. The paper shows that the filter is easy to design, efficient to implement, and it enables accurate low-level feature analysis of musical tones. We describe several case studies to demonstrate the effectiveness of the proposed approach: isolating a single partial from a synthetic signal, analyzing the even-to-odd ratio of harmonics in a clarinet tone, and extracting the residual from a bowed string tone.