EP0542585B1 - Verfahren zur Quantisierung eines Prädiktionsfilters für einen Vocoder mit einer niedrigen Bitrate - Google Patents

Verfahren zur Quantisierung eines Prädiktionsfilters für einen Vocoder mit einer niedrigen Bitrate Download PDF

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Publication number
EP0542585B1
EP0542585B1 EP92402716A EP92402716A EP0542585B1 EP 0542585 B1 EP0542585 B1 EP 0542585B1 EP 92402716 A EP92402716 A EP 92402716A EP 92402716 A EP92402716 A EP 92402716A EP 0542585 B1 EP0542585 B1 EP 0542585B1
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Prior art keywords
filter
frame
coefficients
filters
frames
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EP92402716A
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French (fr)
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EP0542585A3 (de
EP0542585A2 (de
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Pierre-André Thomson-CSF 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
    • G10L19/04—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
    • G10L19/06—Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients

Definitions

  • the present invention relates to a method for quantifying a predictor filter for vocoder at very low flow.
  • 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 finds the standard filter closest to the ideal filter.
  • the advantage is in the reduction in bit rate that is achieved, only 10 to 15 bits per filter being transmitted instead of the 41 bits required in quantization mode scalar, but this flow reduction is obtained at the cost of one very large increase in the memory size required to store the dictionary and significant computational load due to complexity of the filter search algorithm in the dictionary.
  • the object of the invention is to overcome the aforementioned drawbacks.
  • the invention relates to a quantification method a predictive filter for very low bit rate vocoder characterized in that that it consists in sharing the speech signal in packets of a number determined from frames of constant time length by assigning to each frame a weight depending on the average signal strength of speech in the frame, to determine for each frame the coefficients correspondents of the predictor filter by taking those already determined in neighboring frames if its weight is similar to at least one of the frames neighbors or by calculating these in isolation or by interpolation from coefficients of neighboring filters in other cases.
  • the main advantage of the process according to the invention is that it does not requires no prior learning to form a dictionary and that it is therefore indifferent to the type of speaker, the language used or to the frequency response of the analog parts of the vocoder. He has also the advantage of presenting, for a complexity of reasonable performance quality of speech signal reproduction acceptable depending only on the quality of the analysis algorithms speech used.
  • the method according to the invention which is represented by the flowchart of Figure 1 is based on the principle that it is not useful to transmit the coefficients of the prediction filter too often and that it is rather necessary adapt the transmission to what the ear can perceive.
  • the filter coefficients renewal rate is reduced to transmit the coefficients every 30 milliseconds for example instead of every 22.5 milliseconds as is usually realized in standard solutions.
  • the method according to the invention takes account of the fact that the spectrum of the speech signal is generally correlated from one frame to another by grouping together several frames before any coding.
  • the base of coefficients used contains a set of p coefficients easy to quantify by quantization scalar efficient.
  • the prediction filter is represented in the form of a set of p coefficients obtained from the original sampled speech signal possibly pre-emphasized. These coefficients are the reflection coefficients denoted K i which best model the vocal tract. Their absolute value is chosen to be less than one so that the stability condition of the prediction filter is always respected. When these coefficients have an absolute value close to 1, these are finely quantified to take account of the fact that the frequency response of the filter then becomes very sensitive to the slightest error.
  • the method consists firstly in distorting in step 1 in a non-linear manner the reflection coefficients by transforming them into area coefficients denoted LAR i of the Anglo-Saxon abbreviation LOG AREA RATIO, by the relation:
  • the advantage of using the LAR coefficients is that they are more convenient to process than the coefficients K i since their value is always between - ⁇ and + ⁇ and that by quantifying them linearly the same results can be obtained only by using a non-linear quantification of the coefficients K i .
  • the analysis in principal components of the point cloud having the coefficients LAR i as coordinates in a space with P dimensions shows, as represented in a simplified way in the space with two dimensions of figure 2, privileged directions which is taken into account in the quantification to make it more efficient.
  • V 1 , V 2 etc V P are eigenvectors of the autocorrelation matrix of the LAR coefficients
  • an efficient quantification is obtained by considering the projections of the sets of LAR coefficients on the eigenvectors.
  • the quantification takes place in steps 2 and 3 on quantities ⁇ i such that:
  • 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 .
  • each frame is assigned to step 4 by a weight W t (t being between 1 and L), which is an increasing function of the acoustic importance of each frame t considered.
  • W t being between 1 and L
  • the weighting rule takes into account the sound level of the frame concerned because the higher the sound level of a frame compared to the neighboring frames, the more the latter attracts attention, as well as the resonant state or not of the filters, only resonant filters being suitably quantified.
  • Equation (3) P t denotes the average power of the speech signal in each frame of index t and K t, i denotes the reflection coefficients of the corresponding predictor filter.
  • the denominator of the previous expression in parentheses represents the inverse of the gain of the prediction filter, this gain being high when the filter is resonant.
  • the function F is an increasing monotonic function incorporating a regulation mechanism to avoid that certain frames have too low or too high a weight compared to their neighbors.
  • a rule for determining the weights W t can be to adopt for the frame of index t that the quantity F is greater than twice the weight W t-1 of the frame t-1, in this case the weight W t is determined to be twice the weight W t-1 .
  • the weight W t can be taken equal to half the weight W t- 1 . Finally for the other cases, the weight W t can be made equal to F.
  • An example of grouping is shown in Figure 3. For all six frames shown it appears that frames 1 and 2 are combined and quantized together, that the filters in frames 4 and 6 are quantized in isolation and that the filters of frames 3 and 5 are obtained by interpolation. In this diagram, the shaded rectangles represent the quantized filters, the circles represent the true filters and the dashed lines the interpolations.
  • the number of possible configurations is represented by the table of figure 4. On this table the figures 1, 2 or 3 placed in the configuration column indicate respective groupings of 1, 2 or 3 successive filters and the number 0 indicates that the current filter is obtained by interpolation.
  • n 84 filter quantization bits are available in a packet of six frames corresponding to 14 bits on average per frame and if n 1 , n 2 and n 3 denote the numbers of bits allocated to the three quantized filters, these numbers can be chosen from the values 24, 28, 32 and 36 so that their sum is equal to 84 which gives ten possibilities in total.
  • the way of choosing the numbers n 1 , n 2 and n 3 is then considered as a sub-quantification scheme to use the example above in Figure 3.
  • the quantities E Nj are preferably calculated once and for all and which makes it possible to store them for example in a read only memory.
  • the contribution of a given filter of rank t to the total quantization error is obtained by taking into account three factors which are, the weight W t which acts as a multiplicative factor, the deterministic error possibly committed in replacing it with an average filter shared with its neighbor or neighbors, and the theoretical quantization error E Ng calculated previously which depends on the number of quantization bits used. So if F is the filter by which the filter F t of frame t is replaced, the contribution of the filter of frame t to the total quantization error verifies an expression of the form:
  • the quantization error associated with these filters is, by omitting the coefficients W t associated with them, the sum of the interpolation error, i.e. the distance between each filter interpolated and the filter of the frame T, D (F I , F t ) and of the weighted sum of the quantization errors of the two filters F 1 and F 2 , from which the interpolation is made, namely: ⁇ 2 IN 1 ) + (1 - ⁇ ) 2 IN 2 ) if the two filters are quantized with N 1 and N 2 bits respectively.
  • This method of calculation makes it possible to obtain the total quantization error from the quantized filters alone by making for each quantized filter K the sum of the quantization error due to the use of N k bits weighted by the weight of the filter K, (this weight can be the sum of the weight of the filters which it averages if this is the case), of the quantization error induced on the filter or filters which it serves to interpolate weighted by a function of the one or more coefficients ⁇ and the weight (s) of the filter (s) in question and of the deterministic error made deliberately by replacing certain filters with their weighted average and by interpolating others.
  • a stack can then be created which contains only the diagrams of quantification giving the smallest errors and which alone are likely to give good results. Typically, it can be retained about a third of the original quantification schemes.
  • the second pass which is represented at 9 in FIG. 5 aims to select the quantization sub-diagrams (distributions of the numbers of bits allocated to the different filters to be quantified) which give the best results, for the only quantization schemes used.
  • This selection goes through the calculation of fictitious weights ⁇ i which are calculated for the only filters which are to be quantified (possibly composite filters) taking into account neighboring filters obtained by interpolation. Once these fictitious weights have been calculated, a second stack of smaller size is created which contains only the pairs (quantization scheme + sub-schemes), for which the sum of the deterministic error and the quantization error ( weighted by notional weights) is minimal.
  • the predictor filter is then entirely described by a transform in z, P ( z ) such that: in which the coefficients a i are calculated iteratively from the reflection coefficients K i deduced from the coefficients LAR, themselves deduced from the coefficients ⁇ by reversing the relations (1) and (2) described above.
  • the prediction error then checks the relationship: with

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Human Computer Interaction (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
  • Time-Division Multiplex Systems (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Claims (6)

  1. Verfahren zur Quantifizierung eines Vorhersagefilters für einen Vocoder mit sehr geringem Durchsatz, wobei das Sprachsignal in Pakete einer bestimmten Anzahl von Abschnitten konstanter Dauer unterteilt wird und jedem Abschnitt eine Gewichtung abhängig von der mittleren Leistung des Sprachsignals in dem Abschnitt zugewiesen wird (4), dadurch gekennzeichnet, daß für jeden Abschnitt die entsprechenden Koeffizienten des Vorhersagefilters bestimmt werden, indem die bereits in den benachbarten Abschnitten bestimmten Koeffizienten genommen werden (5), wenn die Gewichtung mindestens einem der Nachbarabschnitte ähnlich ist, oder indem die Koeffizienten getrennt (6) oder durch Interpolation (7) ausgehend von den Koeffizienten der Nachbarfilter in den anderen Fällen berechnet werden.
  2. Verfahren nach Anspruch 1, dadurch gekennzeichnet, daß es darin besteht, in jedem Paket von Abschnitten das Filter mit unterschiedlichen Anzahlen von Bits abhängig von den Zusammenfassungen zwischen Abschnitten zu quantifizieren, um die Koeffizienten des Filters zu berechnen, wobei die Summe der Anzahl von in jedem Paket verfügbaren Quantifizierungsbits konstant bleibt.
  3. Verfahren nach Anspruch 2, dadurch gekennzeichnet, daß die Anzahl von Quantifizierungsbits des Filters in jedem Abschnitt bestimmt wird, indem eine Distanzmessung zwischen Filtern durchgeführt wird, um das Filter nur mit den Koeffizienten zu quantifizieren, die einen geringsten Gesamtquantifizierungsfehler ergeben.
  4. Verfahren nach Anspruch 3, dadurch gekennzeichnet, daß die Distanzmessung vom euklidischen Typ ist.
  5. Verfahren nach Anspruch 3, dadurch gekennzeichnet, daß die Distanzmessung vom Typ Itakura-Saito ist.
  6. Verfahren nach Anspruch 2, dadurch gekennzeichnet, daß es darin besteht, in jedem Abschnitt eine bestimmte Anzahl von Quantifizierungs-Unterschemata mit möglichst geringen Fehlern auszuwählen (8), in jedem ausgewählten Unterschema eine fiktive Abschnittsgewichtung unter Berücksichtigung der Nachbarfilter zu berechnen (9) und nur dasjenige Unterschema endgültig zu verwenden (10), dessen Quantifizierungsfehler, gewichtet mit der fiktiven Gewichtung, einen Mindestwert hat.
EP92402716A 1991-10-15 1992-10-06 Verfahren zur Quantisierung eines Prädiktionsfilters für einen Vocoder mit einer niedrigen Bitrate Expired - Lifetime EP0542585B1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR9112669A FR2690551B1 (fr) 1991-10-15 1991-10-15 Procede de quantification d'un filtre predicteur pour vocodeur a tres faible debit.
FR9112669 1991-10-15

Publications (3)

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EP0542585A2 EP0542585A2 (de) 1993-05-19
EP0542585A3 EP0542585A3 (de) 1993-06-09
EP0542585B1 true EP0542585B1 (de) 1998-02-04

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EP92402716A Expired - Lifetime EP0542585B1 (de) 1991-10-15 1992-10-06 Verfahren zur Quantisierung eines Prädiktionsfilters für einen Vocoder mit einer niedrigen Bitrate

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US (1) US5522009A (de)
EP (1) EP0542585B1 (de)
JP (1) JPH0627998A (de)
CA (1) CA2080572C (de)
DE (1) DE69224352T2 (de)
FR (1) FR2690551B1 (de)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2738383B1 (fr) * 1995-09-05 1997-10-03 Thomson Csf Procede de quantification vectorielle de vocodeurs bas debit
US5682462A (en) * 1995-09-14 1997-10-28 Motorola, Inc. Very low bit rate voice messaging system using variable rate backward search interpolation processing
US5950151A (en) * 1996-02-12 1999-09-07 Lucent Technologies Inc. Methods for implementing non-uniform filters
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
US6681203B1 (en) * 1999-02-26 2004-01-20 Lucent Technologies Inc. Coupled error code protection for multi-mode vocoders
FR2799592B1 (fr) 1999-10-12 2003-09-26 Thomson Csf Procede de construction et de codage simple et systematique de codes ldpc
US6735561B1 (en) 2000-03-29 2004-05-11 At&T Corp. Effective deployment of temporal noise shaping (TNS) filters
US7099830B1 (en) * 2000-03-29 2006-08-29 At&T Corp. Effective deployment of temporal noise shaping (TNS) filters
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
DE60208426T2 (de) * 2001-11-02 2006-08-24 Matsushita Electric Industrial Co., Ltd., Kadoma Vorrichtung zur signalkodierung, signaldekodierung und system zum verteilen von audiodaten
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
FR2832880B1 (fr) * 2001-11-23 2004-04-09 Thales Sa Procede et dispositif d'egalisation par blocs avec adaptation au canal de transmission
US8219391B2 (en) * 2005-02-15 2012-07-10 Raytheon Bbn Technologies Corp. Speech analyzing system with speech codebook
JP5649524B2 (ja) * 2011-06-27 2015-01-07 日本電信電話株式会社 映像符号化方法，装置，映像復号方法，装置およびそれらのプログラム
CN112504163B (zh) * 2020-12-11 2022-08-02 北京首钢股份有限公司 热轧带钢横段面的轮廓曲线获取方法、装置及电子设备

Family Cites Families (7)

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Publication number Priority date Publication date Assignee Title
US3715512A (en) * 1971-12-20 1973-02-06 Bell Telephone Labor Inc Adaptive predictive speech signal coding system
JPS60116000A (ja) * 1983-11-28 1985-06-22 ケイディディ株式会社 音声符号化装置
IT1180126B (it) * 1984-11-13 1987-09-23 Cselt Centro Studi Lab Telecom Procedimento e dispositivo per la codifica e decodifica del segnale vocale mediante tecniche di quantizzazione vettoriale
US4815134A (en) * 1987-09-08 1989-03-21 Texas Instruments Incorporated Very low rate speech encoder and decoder
US4852179A (en) * 1987-10-05 1989-07-25 Motorola, Inc. Variable frame rate, fixed bit rate vocoding method
FR2654542B1 (fr) * 1989-11-14 1992-01-17 Thomson Csf Procede et dispositif de codage de filtres predicteurs de vocodeurs tres bas debit.
US5274739A (en) * 1990-05-22 1993-12-28 Rockwell International Corporation Product code memory Itakura-Saito (MIS) measure for sound recognition

Also Published As

Publication number Publication date
US5522009A (en) 1996-05-28
FR2690551A1 (fr) 1993-10-29
DE69224352T2 (de) 1998-05-28
EP0542585A3 (de) 1993-06-09
DE69224352D1 (de) 1998-03-12
CA2080572A1 (en) 1993-04-16
EP0542585A2 (de) 1993-05-19
CA2080572C (en) 2001-12-04
JPH0627998A (ja) 1994-02-04
FR2690551B1 (fr) 1994-06-03

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