Orange

France Telecom

Julien Faure

Stephane Ragot

Pierrick Philippe

Stéphane Ragot

Alexandre Guerin

Claude Marro

Adrien Leman

Marc Emerit

Rozenn Nicol

Jerome Daniel

Grégory Pallone

Jérôme Daniel

Christian Wipliez

Gregory Pallone

Cyril Plapous

A method for decoding a digital signal encoded using predictive coding and transform coding, comprising the following steps: predictive decoding of a preceding frame of the digital signal, encoded by a set of predictive coding parameters; detecting the loss of a current frame of the encoded digital signal; generating by prediction, from at least one predictive coding parameter encoding the preceding frame, a frame for replacing the current frame; generating by prediction, from at least one predictive coding parameter encoding the preceding frame, an additional segment of digital signal; temporarily storing said additional segment of digital signal.

Frame loss management in an FD/LPD transition context

A method of determining a distribution of bits for coding a transition frame, said method being implemented in a coder/decoder for coding/decoding a digital signal, the transition frame being preceded by a predictive coded preceding frame, coding the transition frame comprising transform coding and predictive coding a single sub-frame of the transition frame, the method comprising the following steps: assigning a bit rate for predictive coding the transition sub-frame, said bit rate being equal to the minimum between the bit rate for transform coding the transition frame and a first predetermined bit rate value; determining a first number of bits allocated for predictive coding the transition sub-frame for said bit rate; and calculating a second number of bits allocated for transform coding the transition frame from the first number of bits and a number of bits available for coding the transition frame.

Determining a budget for LPD/FD transition frame encoding

A method for processing a digital audio signal, including a series of samples distributed in consecutive frames, is implemented when decoding the signal in order to replace at least one signal frame lost during decoding. The method includes the following steps: a) searching, in a valid signal segment available when decoding, for at least one period in the signal, determined in accordance with the valid signal; b) analyzing the signal in the period, in order to determine spectral components of the signal in the period; c) synthesizing at least one frame for replacing the lost frame, by construction of a synthesis signal from: an addition of components selected among the predetermined spectral components, and a noise added to the addition of components. In particular, the amount of noise added to the addition of components is weighted in accordance with voice information of the valid signal, obtained when decoding.

Frame loss correction with voice information

A method and device are provided for coding or decoding a digital audio signal by transform using analysis or synthesis weighting windows applied to sample frames. The method includes an irregular sampling of an initial window provided for a transform of given initial size N, to apply a secondary transform of size M different from N.

Coding and decoding devices and methods using analysis or synthesis weighting windows for transform coding or decoding

Methods and apparatus are provided for coding and decoding a digital audio signal. Decoding includes: decoding according to an inverse transform decoding of a previous frame of samples of the digital signal, which is received and coded according to a transform coding; and decoding according to a predictive decoding of a current frame of samples of the digital signal, which is received and coded according to a predictive coding. The predictive decoding of the current frame is a transition predictive decoding which does not use any adaptive dictionary arising from the previous frame. At least one state of the predictive decoding is reinitialized to a predetermined default value, and an add-overlap step combines a signal segment synthesized by predictive decoding of the current frame and a signal segment synthesized by inverse transform decoding, corresponding to a stored segment of the decoding of the previous frame.

Transition from a transform coding/decoding to a predictive coding/decoding

A method for processing a digital signal, implemented during decoding of the signal, in order to replace a succession of samples lost during decoding, the method comprising steps of: generating a structure of a signal for replacing the lost succession, this structure comprising spectral components determined from valid samples received during decoding before the succession of lost samples; generating a residue between a digital signal available to the decoder, comprising received valid samples, and a signal generated from the spectral components; and extracting blocks from the residue, method in which window weighted blocks are injected into the structure using an overlap-add approach, the injected blocks partially overlapping in time.

Frame loss correction by weighted noise injection

A method and device are provided for filtering digital audio signals using at least one ARMA filter, particularly during a filter change. The method includes the following steps: a step of receiving a first request to change filtering to or from filtering by a first ARMA filter; and, in response to the first request, a step of gradually switching, at each of a plurality of cascaded first filtering blocks, between digital-signal filtering by a first basic filtering cell and digital-signal filtering by another associated basic filtering cell, the first basic filtering cells of the plurality of first filtering blocks factorizing the first filter.

Method and device for filtering during a change in an ARMA filter

A signal processing device, media, and method are provided, where a signal comprises a succession of samples distributed in successive frames. The processing is implemented during decoding of such a signal in order to replace at least one signal frame lost in decoding, and comprising in particular: a) searching, in a valid signal available to the decoder, for a signal segment of length corresponding to a period set as a function of the valid signal; b) analyzing a spectrum of the segment in order to determine spectral components of the segment; and c) synthesizing at least one replacement frame for the lost frame by construction of a synthesized signal from at least a portion of the spectral components.

Correction of frame loss during signal decoding

Adaptations of analysis or synthesis weighting windows for transform coding or decoding

A method is provided for determining an indicator evaluating the voice quality of a coded speech signal. The method includes the following steps: calculation per signal frame, of a predetermined number of coefficients of a linear prediction filter for the coded speech signal; determination per frame, of a speech signal reconstructed on the basis of the filter coefficients thus calculated; obtaining per sample, of the residual between the coded speech signal and the reconstructed speech signal; calculation of an evaluation indicator on the basis of the mean or the absolute value of the residuals obtained for all the samples. Also provided are a device for determining an indicator implementing the above method, a method of evaluating the quality or of identifying the class of coding of the coded signal using the indicator determined, as well as a measurement terminal implementing these methods.

Evaluation of the voice quality of a coded speech signal

The invention concerns sound spatialization with multichannel encoding for binaural reproduction on two loudspeakers, the spatial encoding being defined by encoding functions associated with multiple encoding channels and the decoding by applying filters for binaural reproduction. The invention provides for an optimization as follows: a) obtaining a original set of acoustic transfer functions particular to an individual's morphology (HRIR;HRTF), b) selecting spatial encoding functions (g(&#x3b8;,&#x3c6;,n)) and/or decoding filters (F(t,n)), and c) through successive iterations, optimizing the filters associated with the selected encoding functions or the encoding functions associated with the selected filters, or jointly the selected filters and encoding functions, by minimizing an error (c(HRIR,HRIR*)) calculated based on a comparison between: the original set of transfer functions (HRIR), and a set of reconstructed transfer functions (HRIR*) from encoding functions and decoding filters, whether optimized and/or selected.

Optimization of binaural sound spatialization based on multichannel encoding

A method and device are provided for detecting acoustic shocks in an audio stream. The method includes: breaking down the audio stream into audio frames; analyzing the audio frames in order to assign each audio frame a category value from among a plurality of predefined values; and determining the probability of an acoustic shock occurring in a current frame, based on a sequence of a given length of category values assigned to a set of frames, using a two-state Markov model, defined by a predetermined transition matrix and transmission matrix.

Method and device for detecting acoustic shocks

Embodiments of methods and devices for classifying background noise contained in an audio signal are disclosed. In one embodiment, the device includes a module for extracting from the audio signal a background noise signal, termed the noise signal. Also included is a second that calculates a first parameter, termed the temporal indicator. The temporal indicator relates to the temporal evolution of the noise signal. The second module also calculates a second parameter, termed the frequency indicator. The frequency indicator relates to the frequency spectrum of the noise signal. Finally, the device includes a third module that classifies the background noise by selecting, as a function of the calculated values of the temporal indicator and of the frequency indicator, a class of background noise from among a predefined set of classes of background noise.

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Ploubezre, France

Julien Faure