This article is concerned with the estimation of the fundamental frequencies of the quasiharmonic sources in polyphonic signals for the case that the number of sources is known. We propose a new method for jointly evaluating multiple F0 hypotheses based on three physical principles: harmonicity, spectral smoothness and synchronous amplitude evolution within a single source. Given the observed spectrum a set of F0 candidates is listed and for any hypothetical combination among the candidates the corresponding hypothetical partial sequences are derived. Hypothetical partial sequences are then evaluated using a score function formulating the guiding principles in mathematical forms. The algorithm has been tested on a large collection of arti cially mixed polyphonic samples and the encouraging results demonstrate the competitive performance of the proposed method.

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We describe a novel algorithm for the estimation of the colored noise level in audio signals with mixed noise and sinusoidal components. The noise envelope model is based on the assumptions that the envelope varies slowly with frequency and that the magnitudes of the noise peaks obey a Rayleigh distribution. Our method is an extension of a recently proposed approach of spectral peak classification of sinusoids and noise, which takes into account a noise envelope model to improve the detection of sinusoidal peaks. By means of iterative evaluation and adaptation of the noise envelope model, the classification of noise and sinusoidal peaks is iteratively refined until the detected noise peaks are coherently explained by the noise envelope model. Testing examples of estimating white noise and colored noise are demonstrated.

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This paper is about multiple-F0 tracking and the estimation of the number of harmonic source streams in music sound signals. A source stream is understood as generated from a note played by a musical instrument. A note is described by a hidden Markov model (HMM) having two states: the attack state and the sustain state. It is proposed to first perform the tracking of F0 candidates using a high-order hidden Markov model, based on a forward-backward dynamic programming scheme. The propagated weights are calculated in the forward tracking stage, followed by an iterative tracking of the most likely trajectories in the backward tracking stage. Then, the estimation of the underlying source streams is carried out by means of iteratively pruning the candidate trajectories in a maximum likelihood manner. The proposed system is evaluated by a specially constructed polyphonic music database. Compared with the frame-based estimation systems, the tracking mechanism improves significantly the accuracy rate.

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This paper is about the use of perceptual principles for melody estimation. The melody stream is understood as generated by the most dominant source. Since the source with the strongest energy may not be perceptually the most dominant one, it is proposed to study the perceptual properties for melody estimation: loudness, masking effect and timbre similarity. The related criteria are integrated into a melody estimation system and their respective contributions are evaluated. The effectiveness of these perceptual criteria is confirmed by the evaluation results using more than one hundred excerpts of music recordings.

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Concatenative synthesis is a practical approach to sound texture synthesis because of its nature in keeping realistic short-time signal characteristics. In this article, we investigate three concatenative synthesis methods for sound textures: concatenative synthesis with descriptor controls (CSDC), Montage synthesis (MS) and a new method called AudioTexture (AT). The respective algorithms are presented, focusing on the identification and selection of concatenation units. The evaluation demonstrates that the presented algorithms are of close performance in terms of quality and similarity compared to the reference original sounds.

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