System for predictive coding/decoding of a digital speech signal by embedded-code adaptive transform

• US 5,583,963 A
• Filed: 01/21/1994
• Issued: 12/10/1996
• Est. Priority Date: 01/21/1993
• Status: Expired due to Term

• Current Assignee: Gula Consulting Limited Liability Company (Intellectual Ventures LLC)
• Original Assignee: Orange S.A.
• Inventors: Lozach, Bruno
• Primary Examiner(s): MacDonald, Allen R.
• Assistant Examiner(s): ONKA, THOMAS
• Application Number:
  US08/184,186
• Time in Patent Office: 1,054 Days
• Field of Search: 395/2.28, 395/2.32, 370/111, 381/36
• US Class Current: 704/219
• CPC Class Codes: G10L 19/0212 using orthogonal transformation
• CPC Class Codes: G10L 2019/0002 Codebook adaptations
• CPC Class Codes: G10L 2019/0003 Backward prediction of gain
• CPC Class Codes: G10L 2019/0005 Multi-stage vector quantisation
• CPC Class Codes: G10L 2019/0011 Long term prediction filters, i.e. pitch estimation

Abstract

A system for predictive coding of a digital speech signal with embedded codes used in any transmission system or for storing speech signals. The coded digital signal (S_n) is formed by a coded speech signal and, if appropriate, by auxiliary data. A perceptual weighting filter is formed by a filter for short-term prediction of the speech signal to be coded, in order to produce a frequency distribution of the quantization noise. A circuit makes it possible to perform the subtraction from the perceptual signal of the contribution of the past excitation signal P⁰_n to deliver an updated perceptual signal P_n. A long-term prediction circuit is formed, as a closed loop, from a dictionary updated by the modelled page excitation r¹ _n for the lowest throughput and makes it possible to deliver an optimal waveform and an associated estimated gain which make up the estimated perceptual signal P¹_n. An orthonormal transform module includes an adaptive transform module and a module for progressive modelling by orthogonal vectors, thus making it possible to deliver indices representing the coded speech signal. A circuit makes it possible to insert auxiliary data by stealing bits from the coded speech signal. Decoding is performed through extraction of datasignal and transmission of indices representing coded speech signal which is modelled at the minimum throughput.

Claims

1. System for predictive coding of a digital signal as an embedded-code digital signal, coded by embedded-code adaptive transformation, in which the coded digital signal comprises a coded speech signal and, if appropriate, an auxiliary data signal inserted into the coded speech signal after coding said digital speech signal, said system comprising:

a perceptual weighting filter driven by a short-term prediction loop delivering a perceptual signal;

;

a long-term prediction circuit delivering an estimated perceptual signal P¹_n, said long-term prediction circuit forming a long-term prediction loop delivering, from said perceptual signal and from an estimated past excitation signal P^O_n, a modelled perceptual excitation signal P_n ;

adaptive transform and quantization means for receiving said modelled perceptual excitation signal, and for generating said coded speech signal, said perceptual weighting filter including a filter, driven by a short-term prediction loop for providing short-term prediction of a speech signal to be coded, for producing a frequency distribution of quantization noise; and

means for subtracting said past excitation signal P⁰_n, from said perceptual signal to deliver an updated modelled perceptual signal P_n,

said long-term prediction circuit being formed, as a closed loop, from a dictionary updated by a modelled past excitation corresponding to the lowest throughput and delivering a waveform, and an estimated gain associated therewith, which make up the estimated perceptual signal,

said adaptive transform and quantization means including an orthonormal transform module including an adaptive orthogonal transformation module and a module for progressive modelling by orthogonal vectors, said means of progressive modelling and said long-term prediction circuit making it possible to deliver indices representing the coded speech signal, said system further including means for inserting auxiliary data, coupled to a transmission channel.

2. Coding system according to claim 1, wherein said adaptive orthogonal transformation module includes:

means for subtracting said estimated past excitation signal from a speech signal to be coded and for delivering a reduced speech signal;

means for inverse perceptual weighting filtering said estimated perceptual signal and delivering a filtered estimated perceptual signal;

means for subtracting said filtered estimated perceptual signal from said reduced speech signal and delivering an excitation signal; and

a perceptual weighting filter receiving said excitation signal and delivering a linear combination of basis vectors obtained from a singular-value decomposition of a matrix representing said perceptual weighting filter.

3. Coding system according to claim 2, wherein said filter comprises, for every matrix W representing the perceptual weighting filter:

a first matrix module U=(U₁, . . . ,U_N); and

a second matrix module V=(V₁, . . . ,V_N), said first and second matrix modules satisfying the relation;

space="preserve" listing-type="equation">U.sup.T WV=D

where U^T denotes the matrix transpose module of the module U and

D is a diagonal matrix module whose coefficients constitute said singular values,

U_i and V_j denoting respectively the i^th left singular vector and the j^th right singular vector, said right singular vectors {V_j } forming an orthonormal basis, thus making it possible to transform the operation for filtering by convolution product by an operation for filtering by a linear combination.

4. Coding system according to claim 1, wherein said orthonormal transform module comprises:

a stochastic transform sub-module constructed by drawing a Gaussian random variable, for initialization;

a module for global averaging over a plurality of vectors arising from a predictive transform coder;

a reordering module;

a Gram-Schmidt processing module for obtaining, after one reiteration of the processing by the preceding modules an orthonormal transform, performed off-line, formed by learning; and

a read-only memory storing said orthonormal transform in the form of transformed vectors.

5. Coding system according to claim 4, characterized in that the said transform is formed by orthonormal waveforms whose frequency spectra are band-pass and relatively ordered, the first waveform of relatively ordered orthonormal waveforms being equal to the normalized optimal waveform arising from the said adaptive dictionary and the first component of estimated gain is equal to the normalized long-term prediction gain.

6. Coding system according to claim 5, wherein said adaptive transformation module includes:

a Householder transformation module receiving said estimated perceptual signal P¹_l consisting of said optimal waveform and of said estimated gain, and said perceptual signal, and generating a transformed perceptual signal P" in the form of a transformed perceptual signal vector with component P"_k

a plurality of N registers for storing said orthonormal waveforms, said plurality of registers forming said read-only memory, each register of rank r including N storage cells, a component of rank k of each vector being stored in a cell of corresponding rank;

a plurality of N multiplier circuits associated with each register forming said plurality of storage registers, each multiplier circuit of rank k receiving, on the one hand, the component of rank k of the stored vector and, on the other hand, the component P"k of the transformed perceptual signal vector of rank k, and delivering the product P"_k ·

f^k_orhth (k) of said transformed perceptual signal vector components; and

a plurality of N-1 summing circuits associated with each register of rank r, each summing circuit of rank k receiving the product of previous rank k-1 delivered by the multiplier circuit of previous rank and the product of corresponding rank k delivered by the multiplier circuit of previous rank and the product of corresponding rank k delivered by the multiplier circuit of like rank k, the summing circuit of highest rank, N-1, delivering a component g(r) of the estimated gain, expressed as gain vector G.

7. System according to claim 1, wherein said module for progressive modelling by orthogonal vector includes:

a module for normalizing the gain vector to generate a normalized gain vector Gk, by comparing the normed value of gain vector G with a threshold value, said normalization module delivering a length signal for said normalized gain vector Gk, destined for a decoder system as a function of the order of modelling; and

a stage for progressive modelling by orthogonal vectors receiving said normalized vector Gk and delivering said indices representing the coded speech signal, said indices being representative of the selected vectors and of their associated gains, transmission of the auxiliary data formed by the indices being performed by overwriting the parts of the frame allocated to said indices and range numbers to form the auxiliary data signal.

8. A system according to claim 1, wherein said indices representing the coded speech signal delivered by said means of progressive modelling and said long-term prediction circuit comprise parameters data modelling an estimated gain G, said estimated gain verifying the relation:

##EQU23## in which Ψ

_k^j(1) designates an optimal vector drawn from a stochastic dictionary of corresponding rank l with

9. ε

[ 1. L], and

θ

₁ designates the gain value associated to said optimal vector;

said parameters data including indices j(1) of the selected optimal vectors as well as number i(1) of the quantization ranges of their associated gain values, and transmission of said parameters data being carried out by overwriting the parts of a frame allocate to said indices and range numbers for 1 ε

[L₁, L₂ -1] and [L₂, L], respectively, wherein L₁ and L₂ designate intermediate values between 1 and L, with 1≦

L₁ ≦

L₂ ≦

L.

11. Decoding system according to claim 9, wherein said modelling means comprises a first module for modelling the speech signal at the minimum throughput, receiving said coded signal directly and delivering a first estimated speech signal S¹_n ;

a second module for modelling said speech signal at an intermediate throughput connected with said extracting means by means for conditional switching by criterion of the value of said indices, and delivering a second estimated speech signal S²_n ; and

a third module for modelling said speech signal at maximum throughput, connected with said extracting means by means for conditional switching by criterion of particular value of said indices and delivering a third estimated speech signal S³_n,

said decoding system further comprising;

a summing circuit receiving said first, said second and said third estimated speech signals and delivering a resultant estimated speech signal;

an adaptive filtering circuit receiving said resultant estimated speech signal and delivering a reproduced estimated speech signal and

a digital/analog converter receiving said reproduced estimated speech signal and delivering an audio frequency reproduced speech signal.

10. A system for predictive decoding by adaptive transform for a digital signal coded with embedded code in which the coded digital signal comprises a coded speech signal and, if appropriate, of an auxiliary data signal inserted into the coded speech signal after coding the latter, said coded speech signal being represented by parameters data modelling an estimated gain G, said estimated gain verifying the relation:

##EQU24## in which Ψ

_k^j(1) designates an optimal vector drawn from a stochastic dictionary of corresponding rank 1 with 1 ε

[1,L], and

θ

₁ designates the gain value associated to said optimal vector;

said parameters data including indices j(1) of the selected optimal vectors as well as number i(1) of the quantization ranges of their associated gain values, said indices comprising received indices received through a transmission carried out by overwriting the parts of a frame allocated to said indices and range numbers for 1ε

[L₁, L₂ -1] and [L₂, L], respectively, wherein L₁ and L₂ designate intermediate values between 1 and L, with 1≦

L₁ ≦

L₂ ≦

L, said system comprising;

means for extracting auxiliary data from said data signal for an auxiliary use and for transmitting said received indices representing said coded speech signal to a modelling means;

said modelling means comprising means for modelling the speech signal from said received indices at a minimum throughput and for modelling the speech signal from said received indices at at least one throughput above said minimum throughput.

12. Decoding system according to claim 10, wherein said each of first, second and third modules comprise an inverse adaptive transformation sub-module followed by an inverse perceptual weighting filter.