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 Gesturally-Controlled Digital Audio Effects
This paper presents a detailed analysis of the acoustic effects of the movements of single-reed instrument performers for specific recording conditions. These effects are shown to be mostly resulting from the difference between the time of arrival of the direct sound and that of the first reflection, creating a sort of phasing or flanging effect. Contrary to the case of commercial flangers – where delay values are set by a LFO (low frequency oscillator) waveform – the amount of delay in a recording of an acoustic instrument is a function of the position of the instrument with respect to the microphone. We show that for standard recordings of a clarinet, continuous delay variations from 2 to 5 ms are possible, producing a naturally controlled effect.
Download Extraction of the excitation point location on a string using weighted least-square estimation of a comb filter delay
This paper focuses on the extraction of the excitation point location on a guitar string by an iterative estimation of the structural parameters of the spectral envelope. We propose a general method to estimate the plucking point location, working into two stages: starting from a measure related to the autocorrelation of the signal as a first approximation, a weighted least-square estimation is used to refine a FIR comb filter delay value to better fit the measured spectral envelope. This method is based on the fact that, in a simple digital physical model of a plucked-string instrument, the resonant modes translate into an all-pole structure while the initial conditions (a triangular shape for the string and a zero-velocity at all points) result in a FIR comb filter structure.
Download Adaptive Effects Based on STFT, Using a Source-Filter Model
This paper takes the opportunity of presenting a set of new adaptive effects to propose a generic scheme for adaptive effects built upon a spectral source-filter decomposition and a Short-Time Fourier analysis-resynthesis. This allows for a better formalization of the involved signal processing algorithms and leads to a simple classification of adaptive effects already presented in the literature, that falls into this category. We discuss the motivation and the advantages of combining source-filter modeling and phase vocoder representation for the design of adaptive digital audio effects. Then we detail the general structure that includes STFT analysis and re-synthesis scheme, the source filter decomposition, and an adaptive control unit composed of a feature extraction system and a sound mapping unit that might be driven by a gestural control section.
Download A Stochastic State-Space Phase Vocoder for Synthesis of Roughness
This paper presents an implementation of the phase vocoder within a Gaussian state-space framework. Rather than formulate the problem as a deterministic evolution of frequencies centered around a given bin, this evolution is treated stochastically by introducing noise into the dynamics matrix of the recursive state equation. This produces effects on the roughness of the input sound, which vary depending on the position within the matrix where the noise is added, how it is propagated throughout the matrix and further by the variance of the noise input.
Download On the control of the phase of resonant filters with applications to percussive sound modeling
Source-filter models are widely used in numerous audio processing fields, from speech processing to percussive/contact sound synthesis. The design of filters for these models—be it from scratch or from spectral analysis—usually involves tuning frequency and damping parameters and/or providing an all-pole model of the resonant part of the filter. In this context, and for the modelling of percussive (non-sustained) sounds, a source signal can be estimated from a filtered sound through a time-domain deconvolution process. The result can be plagued with artifacts when resonances exhibit very low bandwidth and lie very close in frequency. We propose in this paper a method that noticeably reduces the artifacts of the deconvolution process through an inter-resonance phase synchronization. Results show that the proposed method is able to design filters inducing fewer artifacts at the expense of a higher dynamic range.
Download Improved hidden Markov model partial tracking through time-frequency analysis
In this article we propose a modification to the combinatorial hidden Markov model developed in [1] for tracking partial frequency trajectories. We employ the Wigner-Ville distribution and Hough transform in order to (re)estimate the frequency and chirp rate of partials in each analysis frame. We estimate the initial phase and amplitude of each partial by minimizing the squared error in the time-domain. We then formulate a new scoring criterion for the hidden Markov model which makes the tracker more robust for non-stationary and noisy signals. We achieve good performance tracking crossing linear chirps and crossing FM signals in white noise as well as real instrument recordings.
Download Generalization of the derivative analysis method to non-stationary sinusoidal modeling
In the context of non-stationary sinusoidal modeling, this paper introduces the generalization of the derivative method (presented at the first DAFx edition) for the analysis stage. This new method is then compared to the reassignment method for the estimation of all the parameters of the model (phase, amplitude, frequency, amplitude modulation, and frequency modulation), and to the CramérRao bounds. It turns out that the new method is less biased, and thus outperforms the reassignment method in most cases for signalto-noise ratios greater than −10dB.
Download Analysis / Synthesis of Rolling Sounds Using a Source Filter Approach
In this paper, the analysis and synthesis of a rolling ball sound is proposed. The approach is based on the assumption that the rolling sound is generated by a concatenation of micro-impacts between a ball and a surface, each having associated resonances. Contact timing information is first extracted from the rolling sound using an onset detection process. The resulting individual contact segments are subband filtered before being analyzed using linear predictive coding (LPC) and notch filter parameter estimation. The segments are then resynthesized and overlap-added to form a complete rolling sound. This approach is similar to that of [1], though the methods used for contact event detection and filter parameter estimation are completely different.
Download Sparse Atomic Modeling of Audio: a Review
Research into sparse atomic models has recently intensified in the image and audio processing communities. While other reviews exist, we believe this paper provides a good starting point for the uninitiated reader as it concisely summarizes the state-of-the-art, and presents most of the major topics in an accessible manner. We discuss several approaches to the sparse approximation problem including various greedy algorithms, iteratively re-weighted least squares, iterative shrinkage, and Bayesian methods. We provide pseudo-code for several of the algorithms, and have released software which includes fast dictionaries and reference implementations for many of the algorithms. We discuss the relevance of the different approaches for audio applications, and include numerical comparisons. We also illustrate several audio applications of sparse atomic modeling.