Audio Interpolation and Morphing via Structured-sparse Linear Regression

(Abstract to follow

Time-Frequency multipliers for sound synthesis

International audienceTime-frequency analysis and wavelet analysis are generally used for providing signal expansions that are suitable for various further tasks such as signal analysis, de-noising, compression, source separation, ... However, time-frequency analysis and wavelet analysis also provide efficient ways for constructing signals' transformations. They are modelled as linear operators that can be designed directly in the transformed domain, i.e. the time-frequency plane, or the time-scale half plane. Among these linear operators, transformations that are diagonal in the time-frequency or time scale spaces, i.e. that may be expressed by multiplications in these domains, deserve particular attention, as they are extremely simple to implement, even though their properties are not necessarily easy to control. This work is a first attempt for exploring such approaches in the context of the analysis and the design of sound signals. We study more specifically the transformations that may be interpreted as linear time-varying (LTV) systems (often called time-varying filters). It is known that under certain assumptions, the latter may be conveniently represented by pointwise multiplication with a certain time frequency transfer function in the time-frequency domain. The purpose of this work is to examine such representations in practical situations, and investigate generalizations. The originality of this approach for sound synthesis lies in the design of practical operators that can be optimized to morph a given sound into another one, at a very high sound quality

Sound morphing strategies based on alterations of time-frequency representations by Gabor multipliers

International audienceSounds morphing is an important topic in signal processing of musical sounds and covers a wide variety of techniques whose aim is to "interpolate" between two sound signals. We present here an approach based on the alteration of time-frequency representation. Time-frequency analysis is a classical tool in sounds analysis/synthesis. A time-frequency filter can be well-defined as a diagonal signal operator in a Gabor representation of sounds. Processing can be performed by multiplying a time-frequency representation with such a time-frequency filter, called a Gabor mask. After estimating such a Gabor mask between two sounds, we explore strategies to parametrize it for static morphing between two sounds. We then compare such an approach with standard and non standard approaches of morphing as different kind of sounds combination, notably classical means in the time-frequency domain

Analysis of Sound Signals with High Resolution Matching Pursuit

International audienceSound recordings include transients and sustained parts. Their analysis with a basis expansion is not rich enough to represent efficiently all such components. Pursuit algorithms choose the decomposition vectors depending upon the signal properties. The dictionary among which these vectors are selected is much larger than a basis. Matching pursuit is fast to compute, but can provide coarse representations. Basis pursuit gives a better representation but is very expensive in terms of calculation time. This paper develops a high resolution matching pursuit: it is a fast, high time-resolution, time-frequency analysis algorithm, that makes it likely to be used far musical application

A new murine model of osteoblastic/osteolytic lesions from human androgen-resistant prostate cancer

BACKGROUND: Up to 80% of patients dying from prostate carcinoma have developed bone metastases that are incurable. Castration is commonly used to treat prostate cancer. Although the disease initially responds to androgen blockade strategies, it often becomes castration-resistant (CRPC for Castration Resistant Prostate Cancer). Most of the murine models of mixed lesions derived from prostate cancer cells are androgen sensitive. Thus, we established a new model of CRPC (androgen receptor (AR) negative) that causes mixed lesions in bone. METHODS: PC3 and its derived new cell clone PC3c cells were directly injected into the tibiae of SCID male mice. Tumor growth was analyzed by radiography and histology. Direct effects of conditioned medium of both cell lines were tested on osteoclasts, osteoblasts and osteocytes. RESULTS: We found that PC3c cells induced mixed lesions 10 weeks after intratibial injection. In vitro, PC3c conditioned medium was able to stimulate tartrate resistant acid phosphatase (TRAP)-positive osteoclasts. Osteoprotegerin (OPG) and endothelin-1 (ET1) were highly expressed by PC3c while dikkopf-1 (DKK1) expression was decreased. Finally, PC3c highly expressed bone associated markers osteopontin (OPN), Runx2, alkaline phosphatase (ALP), bone sialoprotein (BSP) and produced mineralized matrix in vitro in osteogenic conditions. CONCLUSIONS: We have established a new CRPC cell line as a useful system for modeling human metastatic prostate cancer which presents the mixed phenotype of bone metastases that is commonly observed in prostate cancer patients with advanced disease. This model will help to understand androgen-independent mechanisms involved in the progression of prostate cancer in bone and provides a preclinical model for testing the effects of new treatments for bone metastases

Extraction of spectral peak parameters using a short-time Fourier transform modeling and no-sidelobe windows,

cote interne IRCAM: Depalle97a/National audienceExtraction of spectral peak parameters using a short-time Fourier transform modeling and no-sidelobe windows

Principal differential analysis: A technique for Data reduction and extraction of musical features

cote interne IRCAM: Winsberg99bNone / NoneNational audiencePrincipal differential analysi

On the Estimation of Sinusoidal Parameters Via Parabolic Interpolation of Scaled Magnitude Spectra

International audienceSinusoids are widely used to represent the oscillatory modes of music and speech. The estimation of the sinusoidal parameters directly affects the quality of the representation. A parabolic interpolation of the peaks of the log-magnitude spectrum is commonly used to get a more accurate estimation of the frequencies and the amplitudes of the sinusoids at a relatively low computational cost. Recently, Werner and Germain [1] proposed an improved sinusoidal estimator that performs parabolic interpolation of the peaks of a power-scaled magnitude spectrum. For each analysis window type and size, a power-scaling factor p is pre-calculated via a computationally demanding heuristic. Consequently, the powerscaling estimation method is currently constrained to a few tabulated power-scaling factors for pre-selected window sizes, limiting its practical applications. In this article, we propose a method to obtain the power-scaling factor p for any window size from the tabulated values. Additionally, we investigate the impact of zeropadding on the estimation accuracy of the power-scaled sinusoidal parameter estimator

Fractional delay lines using Lagrange interpolators

cote interne IRCAM: Depalle96a/National audienceMany studies have been undertaken on the modeling of physical systems by means of waveguidefilters. These methods consist mainly in simulating the propagation of acoustic waves with digitaldelay lines. These models are constrained to have a spatial step fixed by the sampling rate whichbecomes a serious drawback when a high spatial resolution in the geometry of the model is neededor when the length of the waveguide needs to vary. One can use digital filters for approximatingthe exact fractional delay, but length variations usually induce audible distortions because of localinstabilities or modification of the filter's structure. Lagrange Interpolation theory leads to FIR filters which approximate fractional delays accordingto a maximally flat error criterion. Major drawbacks of current implementations of LagrangeInterpolator Filters (LIF), such as the Farrow structure, are a high computation cost and a lack ofcontrol over the delay which can only vary in a narrow range of values. Furthermore, there is noexplicit method for shrinking or enlarging the fractional delay line. We propose a new implementation for fractional delay lines based on the formal power seriesexpansion of the exact z-transform. We have developed different fast and modular algorithms forfractional delay lines which make them usable for real-time delay-varying applications.Modularity in the structure is a key point here as it enables one to switch between filters ofdifferent order while preserving the continuity of the z-transform. Thus the delay may vary overan unlimited range of values. Furthermore, any arbitrary integer part of the fractional delay can besimulated by a classical delay line so that the actual size of the fractional delay line may bemaintained within reasonable limits. We have written a real-time implementation in a MAX-FTSenvironment. Different examples will illustrate its time-varying properties and its numericalstability