Classifications

• • 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 vector quantization method for low bit rate vocoders.
• the quantization begins to be only approximately transparent, and that it is necessary to compensate auditively for this artifact by roughly quantifying the filters located in the transitions of the speech signal and finely those corresponding to stable zones.
• the object of the invention is to overcome the aforementioned drawbacks.
• the subject of the invention is a method for vectoring quantification of low bit rate vocoders, characterized in that it consists in determining the field of coding by surrounding by an envelope the point cloud of the auto-correlation matrix of reflection coefficients of the vocal tract modeling filter, to determine the main axes of the volume of interior points to the envelope, to project the coefficients of the autocorrelation matrix on the main axes, to cut the interior volume of the envelope into elementary volumes and to code the coefficients results of the projection according to their coordinates in space defined by the main axes of the volume of points inside the envelope by assigning as code values only those corresponding to the locations of the elementary volumes in which they are found.
• the main advantage of the invention is that it implements a method for quantifying the prediction filters which requires practically no more binary elements to quantify the points representative of the prediction filters than a vector quantization method using a dictionary. while remaining simple, fast, occupying only a reduced memory space.
• Figure 1 a flowchart illustrating the speech coding method implemented by the invention.
• FIG. 2 a two-dimensional vector space showing a distribution of area coefficients derived from the reflection coefficients modeling the vocal tract.
• 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 the implementation of the method according to the invention.
• the coding method according to the invention consists, after cutting the speech signal into frames of constant length of approximately 20 to 25 ms, as is usually the case in vocoders, determining and coding the characteristics of the speech signal on successive frames by determining the energy of the signal P times per frame.
• the synthesis of the speech signal on each frame then takes place by descrambling and decoding the values of the coded characteristics of the speech signal.
• 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 SK on each frame and quantizing the samples on a determined number of bits followed by a pre-emphasis of these samples, the coefficients Kj of a filter of modeling of the vocal tract from autocorrelation coefficients Rj of samples Sf ⁇ according to a relation of the form
• the calculation of the coefficients Kj 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 journal IEEE Transaction on Acoustics Speech, and
• step 2 consists in non-linearly distorting the reflection coefficients by transforming them into area coefficients noted LARj from the Anglo-Saxon abbreviation LOG AREA RATIO by the relation
• the point cloud represented in FIG. 2 in a space with only two dimensions makes appear two privileged directions symbolized by the eigenvectors
• NQ l n / l n 2 (6)
• the quantification method according to the invention applied to this space consists in associating a unique number with each set of integer coordinates xO, yO, zO verifying the relation:
• 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 previous 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), .. ..
• 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.
• V m (A) the volume of a slice with m dimensions (m ⁇ or equal to
• the relation (14) makes it possible to deduce without difficulty a recurrence relation linking two volumes of consecutive dimensions either: ⁇
• the number of points to be quantified can then be obtained from the preceding relationships by considering for example that the quantization step is worth 1 and that the dimensions of the axes Ai are positive integers. This determination can be obtained by successively considering the isolated points (dimension 0), the series of contiguous points (dimension 1), then by iteratively calculating the volumes of dimensions 2 ... N-1.
• a firmware enabling this result to be obtained is provided in Annex 1.
• 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. To perform this processing, the real values of the coordinates Xj 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-
• a firmware for the execution of this coding algorithm is provided in Annex 2.
• the maximum execution time of the previous algorithm can be shortened thanks to the symmetries. Indeed, if CodeO represents the code of the coordinate origin point (00 ...
• 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 Aj 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 may consist in modifying the initialization of the algorithm, the coding and the decoding so as to use only even coordinates.
• Corresponding modified firmware is provided in Annex 4. Codes are transmitted using binary words. However, since 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, that this number is as close as possible to an exact power of two. This can be achieved by adjusting the volume of the ellipsoid by fractional rather than whole axis lengths.
• the fractions representing the axes Aj 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 D3 Q and D3 - j 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.
• V n (A) 0
• ANum n _ ⁇ Num n .-
• vol maxCode - previousV n Preservation of the max values of Num in ascending order, with their associated value V
• ANum Num A n _-j 2 (D)
• Sum n Su m n + 1 + X n IF n> 1 if n> 1, interative computation
• the instructions referenced by (Z) are those to be used when the axes have whole lengths.
• the instructions referenced by (D) relate to networks of points having coordinates with odd and even sums.
• NV a D is replaced by NVp a D
• V a D by Vp_ a _ b and maxNumer a t ) is replaced by maxNumerp a D if the current network is D n o or D n _ ⁇ .
• the variable parity is 0 for D n rj and 1 for D n ⁇ .
• Function REM2 (X) calculates the remainder of the division of X by 2: it is equivalent to X - 2 INT (X / 2). Annex 6
• Vl, n (A) V 1 ⁇ n (A) + 2 ⁇ / 1 ⁇ n . 1 ) (X n . 1 ) END IF ELSE
• V ⁇ , n (A) V 0 ⁇ n (A) + 2 ⁇ / 1 ⁇ n . 1 ) (X n . 1 )
• V 1 ⁇ n (A) V 1 ⁇ n (A) + 2 * V 0l nl) (Xn-l)

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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)

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• 1995
  • 1995-09-05 FR FR9510393A patent/FR2738383B1/fr not_active Expired - Fee Related
• 1996
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  • 1996-09-04 WO PCT/FR1996/001347 patent/WO1997009711A1/fr active IP Right Grant
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