Download A New Score Function for Joint Evaluation of Multiple F0 Hypotheses 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.
Download Concatenative Sound Texture Synthesis Methods and Evaluation 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.
Download Multiple-F0 tracking based on a high-order HMM model 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.