Download Improving Spectral Analysis Precision with an Enhanced Phase Vocoder using Signal Derivatives
The purpose of this presentation is to demonstrate the practical interest of an original improvement of the classic Fourier analysis. The n-th order short-time Fourier Transform (FT^n) extends the classic short-time Fourier transform by also considering the first n signal derivatives. This technique greatly improves Fourier analysis precision not only in frequency and amplitude but also in time, thus minimizing the well-known problem of the trade-off of time versus frequency. The implementation of this analysis method leads to an enhanced phase vocoder particularly well-suited for extracting spectral parameters from the sounds.
Download Musical Sound Effects in the SAS Model
Spectral models provide general representations of sound in which many audio effects can be performed in a very natural and musically expressive way. Based on additive synthesis, these models control many sinusoidal oscillators via a huge number of model parameters which are only remotely related to musical parameters as perceived by a listener. The Structured Additive Synthesis (SAS) sound model has the flexibility of additive synthesis while addressing this problem. It consists of a complete abstraction of sounds according to only four parameters: amplitude, frequency, color, and warping. Since there is a close correspondence between the SAS model parameters and perception, the control of the audio effects gets simplified. Many effects thus become accessible not only to engineers, but also to musicians and composers. But some effects are impossible to achieve in the SAS model. In fact structuring the sound representation imposes limitations not only on the sounds that can be represented, but also on the effects that can be performed on these sounds. We demonstrate these relations between models and effects for a variety of models from temporal to SAS, going through well-known spectral models.
Download Compression of sinusoidal modeling parameters
In this paper we present a technique for lossless compression of the sinusoidal modeling parameters. Compression is indeed useful for embedding spectral sounds in a synthesizer, broadcasting spectral sounds or simply storing many of them on a medium. This technique consists in compressing the frequency and amplitude parameters of each partial by adaptively sub-sampling and encoding their evolutions with time. It can be easily extended to handle spectral envelopes instead of partials, that is two-dimensional structures instead of one-dimensional ones. We have also designed a very compact file format for (compressed) spectral sounds based on this compression scheme.
Download Additive Synthesis Of Sound By Taking Advantage Of Psychoacoustics
In this paper we present an original technique designed in order to speed up additive synthesis. This technique consists in taking into account psychoacoustic phenomena (thresholds of hearing and masking) in order to ignore the inaudible partials during the synthesis process, thus saving a lot of computation time. Our algorithm relies on a specific data structure called “skip list” and has proven to be very efficient in practice. As a consequence, we are now able to synthesize an impressive number of spectral sounds in real time, without overloading the processor.
Download An Efficient Pitch-Tracking Algorithm Using A Combination Of Fourier Transforms
In this paper we present a technique for detecting the pitch of sound using a series of two forward Fourier transforms. We use an enhanced version of the Fourier transform for a better accuracy, as well as a tracking strategy among pitch candidates for an increased robustness. This efficient technique allows us to precisely find out the pitches of harmonic sounds such as the voice or classic musical instruments, but also of more complex sounds like rippled noises.
Download Survey on Extraction of Sinusoids in Stationary Sounds
This paper makes a survey of the numerous analysis methods proposed in order to extract the frequency, amplitude, and phase of sinusoidal components from stationary sounds, which is of great interest for spectral modeling, digital audio effects, or pitch tracking for instance. We consider different methods that improve the frequency resolution of a plain FFT. We compare the accuracies in frequency and amplitude of all these methods. As the results show, all considered methods have a great advantage over the plain FFT.
Download Sinusoidal Parameter Extraction and Component Selection in a non Stationary Model
In this paper, we introduce a new analysis technique particularly suitable for the sinusoidal modeling of non-stationary signals. This method, based on amplitude and frequency modulation estimation, aims at improving traditional Fourier parameters and enables us to introduce a new peak selection process, so that only peaks having coherent parameters are considered in subsequent stages (e.g. partial tracking, synthesis). This allows our spectral model to better handle natural sounds.
Download Enhanced partial tracking using linear prediction
In this paper, we introduce a new partial tracking method suitable for the sinusoidal modeling of mixtures of instrumental sounds with pseudo-stationary frequencies. This method, based on the linear prediction of the frequency evolutions of the partials, enables us to track these partials more accurately at the analysis stage, even in complex sound mixtures. This allows our spectral model to better handle polyphonic sounds.
Download Enhanced Time-Stretching Using Order-2 Sinusoidal Modeling
In this article, we introduce a 2-level sinusoidal model and demon­ strate its aptitude for a challenging digital audio effect: time-stretching without audible artifacts. More precisely, sinusoidal modeling is used at the two levels of the new sound model. We consider the frequency and amplitude parameters of the partials of the classic sinusoidal model as (control) signals, that we propose to model again using a sinusoidal model. This way, higher-level musical structures such as the vibrato and tremolo in the original sound are captured in the “partials of partials” of this order-2 sinusoidal model. We propose then a new time-stretching method, based on this new hierarchical model, which preserves not only the pitch of the original sound, but also its natural vibrato and tremolo.
Download A Generalized Polynomial and Sinusoidal Model for Partial Tracking and Time Stretching
In this article, we introduce a new generalized model based on polynomials and sinusoids for partial tracking and time stretching. Nowadays, most partial tracking algorithms are based on the McAulay-Quatieri approach and use polynomials for phase, frequency, and amplitude tracks. Some sinusoidal approaches have also been proved to work in certain conditions. We will present here an unified model using both approaches, which will allow more flexible partial tracking and time stretching.