EP0850470B1 - Vektorquantisierungsverfahren für vokoder mit niedriger datenrate - Google Patents

Vektorquantisierungsverfahren für vokoder mit niedriger datenrate Download PDF

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Publication number
EP0850470B1
EP0850470B1 EP96930202A EP96930202A EP0850470B1 EP 0850470 B1 EP0850470 B1 EP 0850470B1 EP 96930202 A EP96930202 A EP 96930202A EP 96930202 A EP96930202 A EP 96930202A EP 0850470 B1 EP0850470 B1 EP 0850470B1
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Prior art keywords
points
envelope
process according
coordinates
coefficients
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French (fr)
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EP0850470A1 (de
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Pierre André LAURENT
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Thales SA
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Thomson CSF SA
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/032—Quantisation or dequantisation of spectral components
    • G10L19/038—Vector quantisation, e.g. TwinVQ audio

Definitions

  • the present invention relates to a quantification method illustration of low speed vocoders.
  • the quantification starts to no longer be that approximately transparent, and that it is necessary to compensate auditively this artifact by roughly quantifying the filters located in the transitions of the speech signal and finely those corresponding to stable areas.
  • the method is based on the use of a dictionary containing a determined number of standard filters obtained by learning. It consists in transmitting only the page or index where the most standard filter is located close to the ideal filter.
  • the object of the invention is to overcome the aforementioned drawbacks.
  • the invention relates to a vector quantization method low-speed vocoders according to claim 1.
  • the main advantage of the invention is that it implements a method of quantification of prediction filters which requires practically no more bits to quantify the representative points of the filters prediction that a dictionary vector quantization process while remaining simple, fast realization occupying only a reduced memory space.
  • Figure 1 a flowchart illustrating the speech coding process implemented by the invention.
  • Figure 2 a two-dimensional vector space showing a distribution of area coefficients derived from the reflection coefficients modeling the duct vocal.
  • FIG. 3 an illustration of the coding method according to the invention in a three-dimensional space.
  • FIGS. 4 to 8b of examples of distribution of the coding of points in a three-dimensional space obtained by implementing the method according to the invention.
  • the coding method according to the invention consists, after cutting the speech signal in frames of constant length of about 20 to 25 ms, as this usually takes place in the vocoders, to determine and code the characteristics of the speech signal on successive frames by determining the signal energy P times per frame.
  • the synthesis of the speech signal on each frame then takes place in descrambling and decoding the characteristic values speech signal coded.
  • the steps representative of the coding method according to the invention which are shown in FIG. 1 consist in calculating in step 1, after a step not shown of sampling the speech signal S K on each frame and quantizing the samples on a determined number of bits followed by a pre-emphasis of these samples, the coefficients K i of a filter for modeling the vocal tract from autocorrelation coefficients R i of the samples S K according to a relation of the form
  • the calculation of the coefficients K i is carried out for example by applying the algorithm known to M. LEROUX-GUEGEN, a description of which can be found in the article of the review IEEE Transaction on Acoustics Speech, and Signal Processing June 1977 having for title " A fixed point computation of partial correlation coefficients ". This calculation amounts to inverting a square matrix whose elements are the coefficients R i of the relation (1).
  • the point cloud represented in FIG. 2 in a space with only two dimensions makes appear two privileged directions symbolized by the eigenvectors V 1 and V 2 .
  • a uniform quantification is then carried out between a minimum value ⁇ imini and a maximum value ⁇ imax with a number of bits n i which is calculated by conventional means as a function of the total number N of bits used to quantify the filter and the percentages of inertia corresponding to the eigenvectors V i .
  • the quantification of the coefficients ⁇ i takes place using a distance measurement between filters, the most natural of which is the weighted Eucledean distance of the form: in which the coefficients ⁇ i are a decreasing function of their rank i and are adjusted experimentally.
  • the quantification method according to the invention applied to this space consists in associating a unique number with each set of integer coordinates x0, y0, z0 verifying the relation: x 2 0 X 2 + y 2 0 Y 2 + z 2 0 Z 2 ⁇ 1
  • a first step consists in traversing the x-axis and calculating the total number of points located in the slices of the ellipsoid which are perpendicular to it and intersecting the x-axis at points for which x takes the successive integer values - X, -X + 1, ..., x-2, x-1.
  • the second stage consists in traversing the axis of y by adding to the preceding result the sum of the numbers of points located in the slices of the ellipsoid for which the abscissa is worth x and the ordinate is successively worth -Y (x), - Y (x + 1), ..., y-2, y-1 where Y (x) ⁇ Y and is the largest value for which the point of coordinates (x Y (x), 0) is located in l ellipsoid or its surface.
  • the z axis is traversed by adding to the previous result the sum of the numbers of points located in the slices for which the abscissa is x, the ordinate is y and the altitude is successively -Z ( x, y), -Z (x, y) +1, ..., z-2, z-1 where Z (x, y) ⁇ Z and is the largest value for which the point of coordinates (x, y, Z (x, y) is located in the ellipsoid or its surface.
  • the quantification algorithm according to the invention is deduced from the above example in 3 dimensions.
  • This algorithm consists in accumulating in the code value the number of points encountered starting from a minimum value of the coordinates to arrive at the code value of the point considered.
  • the real values of the coordinates X i are first converted to their nearest integer value.
  • the resulting values are then corrected so as to be sure that the corresponding point is indeed located inside the ellipsoid, because for possibly external points, it is accepted that the quantization error can be greater than that obtained for points inside.
  • An optimum process for dealing with these points would be to find the points that appear closest to the interior of the ellipsoid.
  • the instructions of the previous algorithm must be included in the coding firmware proper by using the volumes V n (A) already calculated.
  • This algorithm consists of an accumulation in the final code of the number of points left behind the coded point of coordinates (X 1 ... X N ) starting from a point of coordinates (0, 0 ... 0, A N ) on the surface of the ellipse and down towards the point to be quantified.
  • a firmware for the execution of this coding algorithm is provided in Annex 2.
  • the dequantification algorithm proceeds by seeking to reconstruct the terms that have been added to give the value of the code knowing that this reconstruction is unique in nature.
  • the previous algorithms can still be modified by considering half-whole rather than whole coordinates.
  • a first possibility may consist in making a quantizer whose axes are twice the size of the axes A i required.
  • a vector of N real values can then be quantified after doubling, using only odd integers.
  • the previous algorithm can then be used, the exit code obtained being converted by a table giving the final code. This transcoding is necessary for the reason that if only about a quarter of the original centroids are to be considered, this reduction does not facilitate the execution of the algorithm.
  • a second possibility can consist in modifying the initialization of the algorithm, the coding and the decoding so as to use only coordinates pairs.
  • Corresponding modified firmware is provided in Annex 4.
  • the codes are transmitted according to binary words. However, as the number of points included inside an ellipsoid has, a priori no reason particular to form an exact power of two, it seems highly desirable to use an optimal number of bits in the formation of the code, let this number be as close as possible to an exact power of two. This can be achieved by adjusting the volume of the ellipsoid by lengths fractional rather than whole axes.
  • the fractions representing the axes A i have a common denominator.
  • the denominator values of 1, 2, 3 are sufficient to easily obtain ellipsoids containing a number of centroids as close as possible with an exact power of two.
  • FIG. 7a and 7b An example of ellipsoidal vector quantization for D 3.0 and D 3.1 is shown in Figures 7a and 7b.
  • the three axes have respectively dimensions 2, 4, 5, that is to say that they are slightly larger than those of the previous examples to obtain a sufficient number of points.
  • Each centroid is connected to its closest neighbors in the same way as in Figures 4 and 6. It can be checked in these figures that the barycenter belongs (figure 7a) or does not belong (figure 7b) to the set centroids.
  • the instructions referenced by (Z) are those to be used when the axes have entire lengths.
  • the instructions referenced by (D) relate to networks of points having coordinates with odd and even sums.
  • NV a, b is replaced by NV p, a, b , V a, b by V p, a, b and maxNumer a, b is replaced by maxNumer p, a, b if the current network is D n0 or D n-1 .
  • the variable parity is 0 for D n0 and 1 for D n1 .
  • the REM2 (X) function calculates the remainder of dividing X by 2: it is equivalent to X - 2 INT (X / 2).

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Claims (9)

  1. Verfahren zur Vektorquantifizierung von Vokodern mit niedrigem Datendurchsatz, dadurch gekennzeichnet, daß es darin besteht, den Kodierbereich zu bestimmen, indem die Wolke von Punkten der Autokorrelationsmatrix der Bereichskoeffizienten (Log.Area Ratio - LARi) des Modellbildungsfilters für den Sprachverlauf mit einer Hülle umgeben wird, dann die Hauptachsen des Volumens von Punkten innerhalb der Hülle zu bestimmen (3), dann die Koeffizienten der Autokorrelationsmatrix auf die Hauptachsen zu projizieren (4), dann das Volumen innerhalb der Hülle in Elementarvolumina zu zerlegen und die sich bei der Projektion ergebenden Koeffizienten abhängig von ihren Koordinaten in dem durch die Hauptachsen des Volumens von Punkten innerhalb der Hülle definierten Raum zu kodieren, indem jeder Gruppe von sich bei der Projektion ergebenden Koeffizienten ein einheitlicher Kodewert zugewiesen wird, der der Stelle des Elementarvolumens entspricht, in dem sich die Gruppe befindet.
  2. Verfahren nach Anspruch 1, dadurch gekennzeichnet, daß es für die Durchführung der Kodierung jedes Punkts darin besteht, das Volumen innerhalb der Hülle in Scheiben senkrecht zu einer ersten Hauptachsenrichtung von einer ersten Endscheibe bis zu einer Scheibe zu zerschneiden, die der letzten Scheibe mit dem zu kodierenden Punkt vorausgeht, indem die Mengen von in jedem aufeinanderfolgenden Abschnitt enthaltenen Punkten akkumuliert werden, worauf der Gesamtzahl von erhaltenen Punkten die Anzahl von in der letzten Scheibe verbleibenden Punkten hinzugefügt wird, um am zu kodierenden Punkt anzukommen.
  3. Verfahren nach einem beliebigen der Ansprüche 1 und 2, dadurch gekennzeichnet, daß die die Wolke von Punkten umgebende Hülle ein Hyper-Ellipsoid ist, das auf den Schwerpunkt der Wolke von Punkten zentriert ist.
  4. Verfahren nach einem der Ansprüche 1 und 2, dadurch gekennzeichnet, daß die die Wolke von Punkten umgebende Hülle eine Pyramidenform besitzt und auf den Schwerpunkt der Wolke von Punkten zentriert ist.
  5. Verfahren nach einem beliebigen der Ansprüche 2 bis 4, dadurch gekennzeichnet, daß es darin besteht, die realen Werte der Koordinaten der zu kodierenden Punkte in ihren nächstliegenden ganzzahligen Wert zu kodieren.
  6. Verfahren nach einem beliebigen der Ansprüche 2 bis 4, dadurch gekennzeichnet, daß es darin besteht, für die Kodierung nur halb-ganze Koordinaten in Betracht zu ziehen.
  7. Verfahren nach einem beliebigen der Ansprüche 2 bis 4, dadurch gekennzeichnet, daß es darin besteht, für die Kodierung nur Koordinaten von geradzahligen oder ungeradzahligen Summen heranzuziehen.
  8. Verfahren nach einem der Ansprüche 1 bis 7, dadurch gekennzeichnet, daß es darin besteht, das Volumen innerhalb der Hülle durch Teillängen von Koordinatenachsen zu justieren.
  9. Verfahren nach Anspruch 8, dadurch gekennzeichnet, daß die Teillängen von Achsen einen gemeinsamen Nenner besitzen.
EP96930202A 1995-09-05 1996-09-04 Vektorquantisierungsverfahren für vokoder mit niedriger datenrate Expired - Lifetime EP0850470B1 (de)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
FR9510393A FR2738383B1 (fr) 1995-09-05 1995-09-05 Procede de quantification vectorielle de vocodeurs bas debit
FR9510393 1995-09-05
PCT/FR1996/001347 WO1997009711A1 (fr) 1995-09-05 1996-09-04 Procede de quantification vectorielle de vocodeurs bas debit

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EP0850470A1 EP0850470A1 (de) 1998-07-01
EP0850470B1 true EP0850470B1 (de) 1999-06-16

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US (1) US6016469A (de)
EP (1) EP0850470B1 (de)
DE (1) DE69602963T2 (de)
FR (1) FR2738383B1 (de)
WO (1) WO1997009711A1 (de)

Families Citing this family (10)

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FR2778041A1 (fr) * 1998-04-24 1999-10-29 Thomson Csf Procede de neutrodynage du tube d'un emetteur
FR2788390B1 (fr) 1999-01-12 2003-05-30 Thomson Csf Emetteur de radiodiffusion en ondes courtes a haut rendement optimise pour les emissions de type numerique
FR2790343B1 (fr) 1999-02-26 2001-06-01 Thomson Csf Systeme pour l'estimation du gain complexe d'un canal de transmission
FR2799592B1 (fr) 1999-10-12 2003-09-26 Thomson Csf Procede de construction et de codage simple et systematique de codes ldpc
FR2815492B1 (fr) * 2000-10-13 2003-02-14 Thomson Csf Systeme et procede de radiodiffusion assurant une continuite de service
FR2826208B1 (fr) 2001-06-19 2003-12-05 Thales Sa Systeme et procede de transmission d'un signal audio ou phonie
FR2826492B1 (fr) * 2001-06-22 2003-09-26 Thales Sa Procede et systeme de pre et de post-traitement d'un signal audio pour la transmission sur un canal fortement perturbe
FR2832880B1 (fr) * 2001-11-23 2004-04-09 Thales Sa Procede et dispositif d'egalisation par blocs avec adaptation au canal de transmission
FR2832879B1 (fr) * 2001-11-23 2006-08-18 Thales Sa Procede et egalisation par segmentations des donnees
FR2832877B1 (fr) * 2001-11-23 2006-08-18 Thales Sa Procede et dispositif d'egalisation par blocs avec interpolation amelioree

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FR2283592A1 (fr) * 1974-08-27 1976-03-26 Thomson Csf Dispositif extracteur de synchronisation et systeme de transmission d'informations comportant un tel dispositif
FR2431229A1 (fr) * 1978-07-12 1980-02-08 Thomson Csf Dispositif de demodulation de signaux modules en deplacement de frequence et systeme de transmission comportant un tel dispositif
FR2546001B1 (fr) * 1983-05-10 1985-07-05 Thomson Csf Demodulateur de signaux, a enveloppe constante et phase continue, modules angulairement par un train de symboles binaires
FR2604318B1 (fr) * 1986-09-23 1989-03-31 Thomson Csf Procede et dispositif de synchronisation symbole et leur application a la demodulation symbole de messages numeriques
FR2605769B1 (fr) * 1986-10-22 1988-12-09 Thomson Csf Operateur polynomial dans les corps de galois et processeur de traitement de signal numerique comportant un tel operateur
FR2605818B1 (fr) * 1986-10-27 1992-09-18 Thomson Csf Codeur-decodeur algebrique de codes en blocs reed solomon et bch, applicable aux telecommunications numeriques
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US4907276A (en) * 1988-04-05 1990-03-06 The Dsp Group (Israel) Ltd. Fast search method for vector quantizer communication and pattern recognition systems
FR2631146B1 (fr) * 1988-05-04 1991-05-10 Thomson Csf Procede et dispositif de codage de l'energie du signal vocal dans des vocodeurs a tres faibles debits
FR2631147B1 (fr) * 1988-05-04 1991-02-08 Thomson Csf Procede et dispositif de detection de signaux vocaux
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FR2654542B1 (fr) * 1989-11-14 1992-01-17 Thomson Csf Procede et dispositif de codage de filtres predicteurs de vocodeurs tres bas debit.
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Also Published As

Publication number Publication date
US6016469A (en) 2000-01-18
DE69602963D1 (de) 1999-07-22
EP0850470A1 (de) 1998-07-01
FR2738383A1 (fr) 1997-03-07
DE69602963T2 (de) 1999-11-04
FR2738383B1 (fr) 1997-10-03
WO1997009711A1 (fr) 1997-03-13

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