EP0796490B1 - Verfahren und vorrichtung zur signalprädiktion für einen sprachkodierer - Google Patents

Verfahren und vorrichtung zur signalprädiktion für einen sprachkodierer Download PDF

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EP0796490B1
EP0796490B1 EP96934902A EP96934902A EP0796490B1 EP 0796490 B1 EP0796490 B1 EP 0796490B1 EP 96934902 A EP96934902 A EP 96934902A EP 96934902 A EP96934902 A EP 96934902A EP 0796490 B1 EP0796490 B1 EP 0796490B1
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vector
signal
vectors
optimal
residual
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EP0796490A1 (de
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Jacques Paulin
Bertrand Ravera
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Koninklijke Philips NV
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Koninklijke Philips Electronics NV
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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
    • G10L19/04—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 predictive techniques
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • 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
    • G10L2019/0001—Codebooks
    • G10L2019/0011—Long term prediction filters, i.e. pitch estimation

Definitions

  • the present invention relates to a method of prediction, in a speech coder called CELP, of the vector signal residual, or residual vector, of the short-term analysis, said signal containing the periodicity information present in a initial voice signal to be coded broken down into successive sub-frames, said prediction being made from optimal excitations predicted for the previous subframe.
  • CELP speech coder comprising on the one hand a filter short-term analysis, which receives an initial voice signal to be coded decomposed into successive subframes and delivers a vector signal residual defining the frequency information present in the initial voice signal, and secondly a device for predicting this residual signal and a prediction error estimation circuit by difference between this residual vector signal and the signal predicted vector, more particularly said prediction.
  • the words emitted by a phonation organ constitute a voice signal which has two types of properties: on the one hand those linked to the mechanism of the perception of this signal by the human hearing aid (finite bandwidth, resolution finite in frequency, sensitivity to resonant frequencies, insensitivity to the phase of the frequency components of the signal, etc ...), and on the other hand those linked to the operating mechanism of the phonation organ (pseudo-periodicity of sounds, structure resonant signal, ).
  • the voice message itself can be considered to be the combination of content information and additional so-called expression information which individual variations in the acoustic presentation of the message. he is obvious that an effective transmission of such a message would undoubtedly involve defining a criterion of loyalty. he is generally more realistic, however, to simply define a perceptual criterion, which makes it possible to recognize the absence of discernible differences between a message sent and the signal received corresponding.
  • the voice signal is, in fact, constituted by variations in air pressure, generated by the vocal tract under the action of the respiratory system which supplies the energy necessary for the production of speech.
  • the air flow out of the lungs is modulated at a so-called fundamental frequency F o with which the production of vowels is associated.
  • This frequency which varies from 70 to 150 hertz approximately for men and from 150 to 400 hertz approximately for women, characterizes so-called voiced sounds (an example of representation of the amplitude A of a voiced sound as a function of time t is given in Figure 1).
  • the air flow then excites in forced oscillations of the cavities of the vocal tract, to the shape of which correspond natural frequencies F 1 , F 2 , F 3 , etc ... called formants.
  • the voice signal also includes signals which do not have the coherence of voiced sounds, but which are similar to noise, emitted by a source without natural frequency, and which do not excite the natural frequencies of the vocal tract. (these sounds are linked to the production of most consonants).
  • the characteristics of the voice signal can be highlighted by a spectral analysis, which shows that the emitted spectrum comprises on the one hand a spectrum of lines (periodic excitations) for the production of the voiced sounds and on the other hand a continuous spectrum (excitations inconsistent) for producing unvoiced sounds.
  • voice signal shows in that its processing with a view to a faithful transmission of the bandwidth it represents leads to manipulate at the level acoustics a considerable data flow. Analysis techniques speech were then developed to reduce considerably this data flow. By eliminating redundancies thus obtained, the voice signal, initially of the type analog, can then after digitization be compressed to bit rates which, due to the compression ratio achieved, allow its transport on current very low speed lines.
  • This coder is based on a principle called analysis by synthesis (in English: linear prediction analysis-by-synthesis coding), which comprises on the one hand an analysis step, to determine the coefficients of the synthesis filter, and on the other hand, a step of analysis by synthesis, which consists in finding or calculating a sequence of excitations minimizing a determined error criterion (we often use the criterion of least squares).
  • analysis by synthesis in English: linear prediction analysis-by-synthesis coding
  • coding mentioned in the draft standard cited known as linear predictive coding excited by codes (in English, C ode E xcited L inear P redictive encoding, or CELP coding, term which we will adopt in the following description), s is based on a simplified model of the speech production mode, according to which, as a first approximation, the voice signal can be modeled by a short-term (voice path) and long-term (voice source) correlation filter having as input an excitation signal.
  • LPC linear prediction filtering
  • a (z) 10 in the case of recommendation G.723
  • LTP long-term analysis
  • the short-term analysis is based on a predictive method in which the basic idea implemented is, knowing an input voice signal or observed signal s (n) (the index n denotes the rank of the sample) , to find a filter which, excited by an excitation signal x (n), will deliver a predicted signal p (n) as close as possible to s (n) and which therefore allows, by difference between s (n) and p (n), to obtain a residual error e (n) as small as possible.
  • the speech coder described in the document G.723 cited above receives a signal consisting of blocks, or frames, comprising 240 samples, with a sampling frequency of 8 kHz, and each frame is assumed to be divided into four subframes of 60 samples each.
  • a filter 1 / A (z) called synthesis filter, which, applied to an excitation signal x (n), allows to obtain a signal p (n) as close as possible to the sampling signal s (n), it is equivalent to searching for a filter A (z), said to be of analysis, whose coefficients are such that the filter output signal is the most bleached possible when this filter is attacked by the signal to transmit (in an ideal encoder, the output signal would be a real white noise).
  • the voice signal it then, to be able to reconstitute it later, transmit the coefficients of the filter A (z) (these coefficients are less consuming coding bits than would be the case transmission of the prediction error or of
  • the first performs a decorrelation of adjacent samples: its purpose is to define the coefficients of the input filter most suitable for obtaining after filtering the signal known, of a residual signal as close as possible to white noise.
  • t (.) And p (.) Denote respectively, the sample concerned in the signal to be modeled and the predicted sample, ⁇ is a gain value, and OLP (in English, O pen L oop P itch) designates the quantity called open-loop voicing period, characteristic of the periodicity of the signal.
  • OLP in English, O pen L oop P itch
  • the determination of the OLP period and that of the gain ⁇ suffices to implement the prediction represented by expression (3).
  • this determination has the form of a direct dependence: to within a gain factor, the sample to be predicted would be equal to one of the samples already occurring.
  • the first component of the first vector of each V-vector is obtained by shifting from (OLP-2 + ⁇ ) in the past, knowing that ⁇ can take the values (-1, 0, 1) for the even subframes and (-1, 0, 1, 2) for odd subframes.
  • the other four vectors of each V-vector are obtained using the first vector by successive shifts of a sample in the direction of increasing times.
  • the operation corresponding to expression (4) is therefore a prediction with linear combination of samples, during which the search for the solution vector is refined by varying the gain ⁇ , for example, in the case of the G project. 723 cited, giving it five distinct values ( ⁇ is the gain vector formed by these five values), and also by adjusting the OLP quantity by a small value ⁇ .
  • the selection, during this research, of the best possible solution vector is made by including in the course of the determination process a step of minimization, in the least squares sense, of the difference between the vector t (n) output from the analysis filter (the coefficients of which will be transmitted) and the solution vectors resulting from the implementation of expression (4).
  • the analysis filter which, having received the voice signal to be transmitted, only delivers a residual signal constituting the periodicity information of this initial voice signal, it is this signal depleted t (n) for which the prediction explained below will be implemented with reference to FIG. 2.
  • the adaptive dictionary therefore contains the excitation vectors candidates for the construction of an approximation of this vector t (not).
  • FIG. 2 shows, in the case of the G.723 project. an example of a prediction device making it possible to implement the principles of determination which have just been described.
  • This device firstly comprises a circuit 20 for storing excitation vectors (this is the adaptive dictionary mentioned above), constructed from the optimal excitation of the preceding sub-frame, that is to say -to say excitations selected during a previous implementation of the same prediction method for previous samples.
  • excitation vectors this is the adaptive dictionary mentioned above
  • OLP + ⁇ CLP (in English, C losed L oop P itch)
  • circuit 20 is followed, in the case where one is in an even subframe and where ⁇ takes for example the three values - 1, 0 and + 1 (this is the case shown in FIG. 2), of channels 30, here three identical channels 30a, 30b, 30c (circuit 20 is followed by four identical channels, referenced so similar, in the case where one is in an odd sub-frame, ⁇ then taking the four values - 1, 0, + 1, + 2).
  • Each of these channels processes the V-vector of the adaptive dictionary which corresponds to the step ⁇ of the channel considered, and includes in this firstly in series effect a filter 31, having as response the impulse response of the synthesis filter (defined above).
  • a circuit 32 also receiving the target vector to be modeled t (n) is then provided for the calculation of a vector with twenty components V ( ⁇ ) consisting of five correlation terms between the filtered vectors and the residual vector (in English: cross-products), given by the scalar products of the five filtered vectors of the adaptive dictionary by the target vector t (n), five energy terms, given by the scalar products of the five filtered vectors of the adaptive dictionary by themselves, and ten two-by-two correlation terms between the filtered vectors. From these correlations, it is possible to determine to what extent the residual vector or target vector t (n) can be modeled from V-vectors of the adaptive dictionary.
  • the gains which are quantized, are provided by a memory 40, or quantization table, which contains the possible values for the various gains (170 to 5.3 kbits / s., And 85 or 170 to 6.3 kbits / s ., the 170 vectors of the table used in one or the other case then being the same).
  • the information relating to the gains is given, in this quantification table, in the form of vectors each having twenty terms (as previously) defined as follows: five gain values, five values equal to the square of these gains, ten values corresponding to the ten two by two of these five gain values.
  • the gain vector ⁇ optimal in the sense of expression (5) is the one which cancels the derivative of ⁇ with respect to each of the components of the vector, and which, by this very fact, maximizes the scalar product of V ( ⁇ ) by a vector from the quantification table.
  • a circuit 50 then allows the selection of the maximum scalar product among the three or four scalar products available at the output of these three (or four) circuits, maximum scalar product to which an optimal value of the step correspondent (stored in a memory 110) and an optimal value of the gain vector ⁇ .
  • the optimal value of ⁇ is of course one of the three (or four) values used in the three (or four) channels, and the value thus selected makes it possible to control a switch 60, comprising as many inputs as there are of tracks (three, or four).
  • This switch provided at the output of the filters 31, makes it possible to select the filtered V-vector constituting the best representative for the desired solution vector.
  • This selected filtered vector is then presented at the input of an amplifier 70 whose gain vector ⁇ , delivered by the selection circuit 50, had been stored in a memory 80 present at the output of this circuit 50.
  • the optimal filtered V-vector thus amplified is the prediction vector p (n) sent to the negative terminal of a subtractor 90 which receives on its positive terminal the vector t (n) output from the CELP encoder analysis filter.
  • a first object of the invention is therefore to propose a simpler prediction method, with almost equal quality, than the one previously described.
  • Another object of the invention is to propose a coder for speech similar to that just described, but with a reduced complexity and while maintaining quality practically equivalent.
  • the solution according to the invention makes it possible to make a much lower number of paths (four in the case of the coder according to this document), with an almost imperceptible deterioration in quality.
  • the basic idea of the structure thus proposed is indeed the following: by making the simplifying assumption that the predictors are decorrelated, or, which is equivalent, that the correlations between filtered vectors taken two by two, previously defined, are zero, we can, for each sub-frame and for each channel corresponding to a step ⁇ , define an initial gain vector ⁇ ( ⁇ ) init , without costly matrix inversion calculation. The components of this vector are then, for the channel considered, the successive ratios of the correlation terms between the filtered vectors and the target vector and the energy terms of the vector V ( ⁇ ) defined previously.
  • the optimal initial step determined for each subframe by the calculation subset provided at the output of ways, is then the one that maximizes one of the three, or four depending on whether the subframe is even or odd, scalar products of ⁇ T ( ⁇ ) init by V ( ⁇ ), determined by the calculation circuit provided for in each channel after the calculation of V ( ⁇ ) (we recall here that V ( ⁇ ) was defined previously, while ⁇ T ( ⁇ ) init is a vector that has the same number of components as V ( ⁇ ), namely, in this case: the five components of the
  • the vector of the optimal gain for each subframe is then obtained using the circuit provided at the output of the quantification table and which performs the search for the maximum value of the scalar product of the vector.
  • V ( ⁇ ) corresponding to the optimal value of the step ⁇ which has just been calculated by each of the vectors (here 170 or 85 depending on the flow) of said table.
  • This determination of the optimal gain vector requires only one scan of the quantization table per subframe, ie four per frame (instead of three or four per subframe depending on whether the subframe is even or odd. , or fourteen per frame), which results in a significant reduction in complexity.
  • the prediction device such as shown in Figure 3, present with that of Figure 2 of common elements, namely the circuit 20 for memorizing the candidate excitation vectors (or adaptive dictionary), filters 31, the circuits 32 for calculating the correlation terms and of energy, memory 40 (or quantization table), switch 60, amplifier 70, memory 80, subtractor 90, and memory 110.
  • the search for the optimal gain vector is then carried out by the selection circuit 150, and the vector thus selected is kept in memory 80.
  • the switch 60 provided at the output of the filters 31 and whose position is controlled by the value of ⁇ issue from memory 110, sends the selected filtered V-vector to amplifier 70.
  • the optimal filtered V-vector thus amplified is the prediction vector p (n), sent, as in the case of FIG. 2, to the subtractor 90.

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

Claims (2)

  1. Prädiktionsverfahren des vektoriellen Restsignals oder Restvektors kurzfristiger Analyse in einem sogenannten CELP-Sprachkodierer, wobei das besagte Signal die Periodizitätsinformation enthält, vorhanden in einem zu kodierenden ursprünglichen Lautsignal, aufgeteilt in aufeinanderfolgende Unterraster, und die besagte Prädiktion anhand von optimalen prädiktiven Stimulationen für das vorhergehende Unterraster durchgeführt wird, und das Verfahren für jedes der besagten Unterraster folgende Schritte umfaßt:
    (1) Für verschiedene Werte eines sogenannten Bestimmungsschrittes δ der besagten Periodizitätsinformation und hinsichtlich der Auswahl, anhand der besagten, zuvor beschriebenen optimalen Stimulationen, eines optimalen Leistungsvektors β opt und des entsprechenden Wertes des optimalen Schrittes, einen Durchführungsschritt in Serie, und für jeden der Werte von δ, folgende Unterschritte:
    (a) einen Unterschritt der Filterung;
    (b) einen Unterschritt der Berechnung der Korrelationsausdrücke zwischen den gefilterten Vektoren und dem Restvektor, der Energieausdrücke der gefilterten Vektoren und der Korrelationsausdrücke zwischen den paarweise genommenen gefilterten Vektoren zur Abgabe eines ersten Vektors V (δ);
    (c) einen Unterschritt der Auswahl zur Bestimmung eines ursprünglichen Leistungsvektors β(δ)init, der Quadrate der Komponenten des besagten Vektors und der Produkte dieser selben paarweise genommenen Komponenten zur Abgabe eines zweiten Vektors β T(δ)init;
    (2) ein Schritt der Auswahl des besagten optimalen Wertes des Schrittes δ, wobei dieser dem Weg entspricht, für den das Skalarprodukt der besagten ersten und zweiten Vektoren V (δ) und β T(δ)init maximal ist, und, für diesen optimalen Wert von (δ), zur Auswahl in einer sogenannten Quantifikationstabelle des besagten optimalen Leistungsvektors β opt, der derjenige der Tabelle ist, für den das Skalarprodukt des besagten ersten Vektors V (δ) für jeden der Vektoren der Tabelle maximal ist;
    (3) ein Schritt zur Berechnung des besagten prädiktiven vektoriellen Restsignals oder prädiktiven Restvektors anhand einerseits der gefilterten Stimulationsvektoren des vorhergehenden Unterrasters, das dem besagten, zuvor ausgewählten optimalen Wert von δ entspricht, und andererseits des besagten ausgewählten optimalen Leistungsvektors.
  2. CELP-Sprachkodierer mit einerseits einem kurzfristigen Analysefilter, der ein ursprüngliches zu kodierendes Lautsignal erhält, aufgeteilt in vier aufeinanderfolgende Unterraster, und ein vektorielles Restsignal t (n) abgibt, zur Definition der im ursprünglichen Lautsignal vorhandenen Periodizität, und andererseits eine Prädiktionsvorrichtung dieses Restsignals und eine Bestimmungsschaltung des Prädiktionsfehlers über die Differenz zwischen diesem vektoriellen Restsignal t (n) und dem prädiktiven vektoriellen Signal p (n), wobei die besagte Prädiktionsvorrichtung enthält:
    (A) Eine Schaltung zum Speichern von Vektoren (20), ein sogenanntes dynamisches Wörterbuch, das für das vorhergehende Raster optimale prädiktive Stimulationen enthält;
    (B) am Ausgang der besagten Speicherschaltung eine Vielzahl an Wegen zur Berechnung (130a, 130b, 130c) eines Vektors β T (δ)init, jeweils parallel für einen bestimmten Wert eines sogenannten Bestimmungsschritts δ der Periodizitätsinformation vorgesehen, die jeweils selbst in Serie enthalten:
    (a) einen Filter (31) mit einer Impulsreaktion gleich der des Synthesefilters, ausgehend von dem besagten Analysefilter gebildet;
    (b) eine Schaltung zur Berechnung (32) der Korrelationsausdrücke zwischen den gefilterten Vektoren, aus dem besagten dynamischen Wörterbuch kommend, und dem besagten Restvektor oder Zielvektor, von Energieausdrücken der gefilterten Vektoren und Korrelationsausdrücken zwischen den paarweise genommenen gefilterten Vektoren;
    (c) eine Schaltung zur Vorauswahl pro Weg (101) des besagten Vektors β(δ)init, dessen Komponenten einerseits die Komponenten eines ursprünglichen Leistungsvektors β(δ)init und andererseits die Quadrate der Komponenten des besagten Vektors sind, und schließlich der Produkte dieser selben, paarweise genommenen Komponenten;
    (C) ein Unterensemble zur Berechnung (102) und Speicherung (110) des optimalen Wertes des besagten Schrittes;
    (D) einen Speicher, eine sogenannte Quantifikationstabelle (40), der die Komponenten der möglichen Leistungsvektoren sowie ihre Quadrate und ihre paarweise Produkte enthält;
    (E) einen Schalter zur Auswahl (161), in Verbindung mit dem besagten optimalen Wert, des Schrittes des entsprechenden optimalen Vektors V (δ), bestehend aus Korrelationsausdrücken, erhalten durch die Skalarprodukte der gefilterten Vektoren über den Restvektor, von Energieausdrücken, erhalten durch die Skalarprodukte der gefilterten Vektoren selbst, und von Korrelationsausdrücken, erhalten durch die paarweisen Skalarprodukte der gefilterten Vektoren;
    (F) eine Schaltung zur Auswahl (150) in der besagten Quantifikationstabelle jedes der möglichen Leistungsvektoren;
    (G) einen Speicher zum Ablegen (80) des so gewählten Leistungsvektor;
    (H) am Ausgang dieses Speichers einen Verstärker (70) des Ausgangs des nach dem besagten Wert des optimalen Schrittes von einem Schalter ausgewählten Filters;
    (I) einen Subtrahierer (90) zur Bestimmung des besagten Prädiktionsfehlers über die Differenz zwischen dem besagten Restsignal t (n) und dem aus dem besagten Verstärker kommenden prädiktiven Signal p (n).
EP96934902A 1995-10-11 1996-10-11 Verfahren und vorrichtung zur signalprädiktion für einen sprachkodierer Expired - Lifetime EP0796490B1 (de)

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EP96934902A EP0796490B1 (de) 1995-10-11 1996-10-11 Verfahren und vorrichtung zur signalprädiktion für einen sprachkodierer

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
FR9511937A FR2739964A1 (fr) 1995-10-11 1995-10-11 Dispositif de prediction de periode de voisement pour codeur de parole
FR9511937 1995-10-11
EP96402030 1996-09-25
EP96402030 1996-09-25
PCT/FR1996/001596 WO1997014139A1 (fr) 1995-10-11 1996-10-11 Methode et dispositif de prediction de signal pour un codeur de parole
EP96934902A EP0796490B1 (de) 1995-10-11 1996-10-11 Verfahren und vorrichtung zur signalprädiktion für einen sprachkodierer

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JP3263347B2 (ja) * 1997-09-20 2002-03-04 松下電送システム株式会社 音声符号化装置及び音声符号化におけるピッチ予測方法

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US4899385A (en) * 1987-06-26 1990-02-06 American Telephone And Telegraph Company Code excited linear predictive vocoder
US5138661A (en) * 1990-11-13 1992-08-11 General Electric Company Linear predictive codeword excited speech synthesizer

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DE69609592D1 (de) 2000-09-07

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