Download Signal Characterization in terms of Sinusoidal and Non-Sinusoidal Components This paper addresses the problem of signal characterization in terms of sinusoidal and non-sinusoidal com-ponents. A first measure of sinusoidality is reviewed. Drawbacks of this sinusoidal estimator are investigated and solutions proposed. Estimation of sinusoidality on non-stationary signal is then made on apre-processed signal. A phase derived sinusoidality measure and the use of Re-estimated Spectra are introduced which allow deriving very precise and local characteristics. Finally, this characterization is used in anew synthesis scheme using Additive and PSOLA synthesis.
Download Vibrato: detection, estimation, extraction, modification This paper deals with vibrato detection, vibrato extraction on f 0 trajectory, and vibrato parameter estimation and modification. Vibrato detection and extraction are aimed at being a first step for note segmentation of singing voice signals. The aim is also to characterize sounds with the descriptor: "presence of vibrato" or "absence of vibrato". Changing vibrato parameters, that is to say its magnitude and its frequency, is also one of the possible musical applications. It is firstly required to detect the presence of vibrato. In order to do that, several approaches are possible: we can analyse directly the sound signal or its f 0 trajectory. For each approach, several techniques exist: some of them are described here: the "spectrum modelling" method, the "spectral envelopes distortion" method, the "AR prediction" method, the "analytic signal" method and the "minima - maxima detection" method. Their performance are compared. Secondly, the parameterization is completed: if there is vibrato, the parameters of the vibrato, that is to say its frequency and its magnitude, are given. Thirdly, the vibrato is extracted on f 0 trajectory to obtain a no-vibrato melodic evolution. This "flat" fundamental frequency is useful for segmentation of musical excerpts into notes, but can also be used for sound modification or processing.
Download Physical Constraints for the Control of a Physical Model of a Trumpet In this paper, the control of a physical model of a trumpet is studied. Although this model clearly describes the mechanical and acoustical phenomena that are perceptually relevant, additional constraints must be imposed on the control parameters. In contrast with the model where the tube length can be varied continuously, only seven different tube lengths can be obtained with a real instrument. By studying the physical model and its implementation, different relationships between the control parameters and signal characteristics are identified. These relationships are then used to obtain the best set of tube lengths with respect to a given tuning frequency.
Download A new estimation technique for determining the control parameters of a physical model of a trumpet A new estimation technique is proposed which computes the control parameters of a physical model of a trumpet in order to simulate a recording of a real instrument. First, the physical constraints of the instrument and the prior knowledge about how a player controls a trumpet are described. This is taken into account during the design of the data set and guarantees that these constraints are respected. Then, an estimation procedure minimizes two perceptual similarity criteria in function of the control parameters. The first criterium expresses the difference of the spectral envelopes and the second one the difference in fundamental frequency. An optimization technique is proposed that yields an optimal solution for the fundamental frequency, and a conditional suboptimal solution for the spectral envelope. A robust implementation of the technique was developed for which it is shown that the estimated parameters are unique and that the optimization does not suffer from local minima.
Download Musical Instrument Identification in Continuous Recordings Recognition of musical instruments in multi-instrumental, polyphonic music is a difficult challenge which is yet far from being solved. Successful instrument recognition techniques in solos (monophonic or polyphonic recordings of single instruments) can help to deal with this task. We introduce an instrument recognition process in solo recordings of a set of instruments (bassoon, clarinet, flute, guitar, piano, cello and violin), which yields a high recognition rate. A large and very diverse solo database (108 different solos, all by different performers) is used in order to encompass the different sound possibilities of each instrument and evaluate the generalization abilities of the classification process. First we bring classification results using a very extensive collection of features (62 different feature types), and then use our GDE feature selection algorithm to select a smaller feature set with a relatively short computation time, which allows us to perform instrument recognition in solos in real-time, with only a slight decrease in recognition rate. We demonstrate that our real-time solo classifier can also be useful for instrument recognition in duet performances, and improved using simple “source reduction”.
Download Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation In this article the estimation of the spectral envelope of sound signals is addressed. The intended application for the developed algorithm is pitch shifting with preservation of the spectral envelope in the phase vocoder. As a first step the different existing envelope estimation algorithms are investigated and their specific properties discussed. As the most promising algorithm the cepstrum based iterative true envelope estimator is selected. By means of controlled sub-sampling of the log amplitude spectrum and by means of a simple step size control for the iterative algorithm the run time of the algorithm can be decreased by a factor of 2.5-11. As a remedy for the ringing effects in the the spectral envelope that are due to the rectangular filter used for spectral smoothing we propose the use of a Hamming window as smoothing filter. The resulting implementation of the algorithm has slightly increased computational complexity compared to the standard LPC algorithm but offers significantly improved control over the envelope characteristics. The application of the true envelope estimator in a pitch shifting application is investigated. The main problems for pitch shifting with envelope preservation in a phase vocoder are identified and a simple yet efficient remedy is proposed.
Download Adaptive Threshold Determination for Spectral Peak Classification A new approach to adaptive threshold selection for classification of peaks of audio spectra is presented. We here extend the previous work on classification of sinusoidal and noise peaks based on a set of spectral peak descriptors in a twofold way: on one hand we propose a compact sinusoidal model where all the modulation parameters are defined with respect to the analysis window. This fact is of great importance as we recall that the STFT spectra are closely related to the analysis window properties. On the other hand, we design a threshold selection algorithm that allows us to control the decision thresholds in an intuitive manner. The decision thresholds calculated from the relationships established between the noise power in the signal and the distributions of sinusoidal peaks assures that all peaks described as sinusoidal will be correctly classified. We also show that the threshold selection algorithm can be used for different types of analysis windows with only a slight parameter readjustment.
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.
Download Automatic Segmentation of the Temporal Evolution of Isolated Acoustic Musical Instruments Sounds Using Spectro-Temporal Cues The automatic segmentation of isolated musical instrument sounds according to the temporal evolution is not a trivial task. It requires a model capable of capturing regions such as the attack, decay, sustain and release accurately for many types of instruments with different modes of excitation. The traditional ADSR amplitude envelope model does not apply universally to acoustic musical instrument sounds with different excitation methods because it uses strictly amplitude information and supposes all sounds manifest the same temporal evolution. We present an automatic segmentation technique based on a more realistic model of the temporal evolution of many types of acoustic musical instruments that incorporates both temporal and spectrotemporal cues. The method allows a robust and more perceptually relevant automatic segmentation of the isolated sounds of many musical instruments that fit the model.