EP2153438B1 - Nachbearbeitung zur reduzierung des quantifizierungsrauschens eines codierers während der decodierung - Google Patents

Nachbearbeitung zur reduzierung des quantifizierungsrauschens eines codierers während der decodierung Download PDF

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EP2153438B1
EP2153438B1 EP08805992A EP08805992A EP2153438B1 EP 2153438 B1 EP2153438 B1 EP 2153438B1 EP 08805992 A EP08805992 A EP 08805992A EP 08805992 A EP08805992 A EP 08805992A EP 2153438 B1 EP2153438 B1 EP 2153438B1
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signal
quantization noise
decoded
rsb
decoded signal
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French (fr)
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EP2153438A1 (de
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Jean-Luc Garcia
Claude Marro
Balazs Kovesi
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Orange SA
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France Telecom 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
    • G10L19/26—Pre-filtering or post-filtering
    • 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
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0316—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude
    • G10L21/0364—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude for improving intelligibility
    • 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
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering

Definitions

  • the present invention relates to signal processing, in particular digital audio signals in the field of telecommunications, these signals being for example speech, music, or other signals.
  • the rate needed to pass an audio and / or video signal with sufficient quality is an important parameter in telecommunications.
  • audio coders have been developed in particular to compress the amount of information necessary to transmit a signal.
  • Some encoders achieve particularly high information compression rates. Such coders generally use advanced information modeling and quantification techniques. Thus, such encoders transmit only models or partial data of the signal.
  • the decoded signal although not identical to the original signal (since some of the information has not been transmitted due to the quantization operation), nevertheless remains very close to the original signal.
  • Quantization noise The difference, from a mathematical point of view, between the decoded signal and the original signal is then called "quantization noise”.
  • disortion introduced by the coding / decoding.
  • a perceptual post-filter of the type used, for example, in CELP type speech decoders (for "Code Excited Linear Prediction"). This is to perform a filtering that improves the subjective quality at the price of a distortion. Indeed, a signal attenuation is applied in the areas where the quantization noise is most audible (especially between the formants).
  • Current perceptual post-filters provide good results for speech signals, but poorer results for other types of signals (music signals, for example).
  • Harmonics and formants are well-known spectral characteristics of speech but applying this type of processing to a signal other than speech generates strong distortions. For example, the spectral richness of a music signal can not be handled with such a simple signal model.
  • perceptual post-filters can generate distortions, because they rely on a model that is not precise enough. Moreover, the perceptual post filter is usually ineffective in periods of silence.
  • the document US2003 / 0182104 describes the modification of a digital audio signal in a decoding step based on a psychoacoustic model. Such a modification would be applicable to the perceptually encoded signals provided that the quantization noise distribution can be derived from the encoded data.
  • Another treatment family targets conventional noise reduction treatments to distinguish the useful signal from the noise.
  • This type of processing therefore makes it possible to reduce the noise related to the environment of the signal capture and it is often used for speech signals.
  • coding / decoding one may want to transmit the ambient noise and it is then desirable that the noise reduction does not apply to this type of noise.
  • the present invention improves the situation.
  • noise reduction processing is understood to mean an operation of the type described above which consists in extracting the useful signal from a signal to be processed, by filtering the parasitic signals, for example by defining a gain function intervening in a filter applied to the decoded signal.
  • the quantization noise is filtered.
  • noise reduction processing specific to each type of compression coding performed.
  • the very way of estimating the characteristics of the noise reduction filter depends on the type of coding performed.
  • the quantization noise itself strongly depends on the type of coding performed. It will be seen that it is possible to establish a variation of the quantization noise as a function of a variation of the decoded signal, and that this variation of the quantization noise is specific to the type of coding implemented.
  • the prior information on the type of compression coding is obtained during an encoder declaration procedure.
  • the invention is particularly suitable in the case where the type of compression coding is a coding according to the G.711 standard.
  • the present invention also provides a device for processing a signal initially coded in compression according to a predetermined type of coding, and then decoded.
  • the device is defined in claim 6.
  • the device advantageously comprises means for implementing the method described above.
  • FIG. figure 1 representing a TBQ device of the aforementioned type downstream of the DEC decoding unit. This figure 1 will be described in detail later.
  • the present invention also relates to a computer program, intended to be stored in memory of a processing device of the aforementioned type, and comprising instructions for calculating the quantization noise, as well as parameters of a quantization noise reduction filter. when these instructions are executed by a processor of the processing device.
  • the instructions on the variation of the quantization noise can be programmed offline, on the basis of observations (theoretical or experimental according to the exemplary embodiments which will be described later) made on the type of coding used.
  • the way in which these instructions are carried out, itself, will be described in detail later, with reference to figures 2 and 5 which can then constitute flowcharts of a computer program within the meaning of the invention.
  • the invention proposes a post-processing performed after decoding and which uses information a priori on the characteristics of the quantization operation performed by the encoder.
  • the type of processing (or "processing model" according to the generic terms above) that will be chosen to process the signal is independent of the characteristics of the signal itself.
  • the processing itself in particular the estimation of the gain function
  • the type of treatment is the same and is not based, for example, on only on the energy of a decoded frame received.
  • the invention makes it possible to reduce the quantization noise (and therefore the distortion) that a compression encoder of the signal implementing a quantization operation usually introduces.
  • the invention advantageously reduces the quantization noise alone, even during periods of silence, and this, for any type of signal.
  • the implementation of the invention does not perform a conventional noise reduction and therefore does not modify the noise related to the environment of the capture of the signal.
  • the implementation of the invention can reduce or eliminate quantization noise without distorting the signal and this for any type of signal, just using a priori information on the type of encoder used (for example the characteristics of the encoder compression model, the characteristics of the quantizer, or other).
  • the present invention finds an advantageous application to the field of speech and music processing, and more generally to the processing of the signal, especially images, since any encoder is required to introduce a quantization noise.
  • the invention applies to all areas where it is sought to reduce a quantization noise of a signal.
  • the signal thus decoded denoted S * , then has a quantization noise which is defined mathematically as a difference (S * - S) with respect to the original signal S.
  • a quantization noise reduction processing unit TBQ is provided, downstream of the decoder DEC, for suppressing or at least limiting the quantization noise in the signal S * .
  • the unit TBQ comprises at least one input E to receive decoder DEC information INF on the type of coding / decoding implemented, which then allows to choose a noise reduction treatment model to be implemented. artwork.
  • it is estimated from the signal received and decoded S * and, depending on the type of coding / decoding that has been implemented, the influence of the quantization noise in the received signal S * .
  • a calculation module is provided to give an estimate of the quantization noise BQ, on the basis of the model chosen and as a function of the received signal S * .
  • This calculation module can typically be in the form of a combination of a processor and a working memory (not shown).
  • the estimated noise BQ is simply processed by applying a conventional filtering FIL to the signal S * to finally output a processed signal S * T.
  • the parameters PAR of the FIL filter applied to the signal S * are determined to reduce in particular the estimated quantization noise BQ.
  • step S3 determining a model (step S3) of noise reduction processing.
  • the quantization noise reduction model chosen may be different, for example depending on whether the signal has been coded / decoded according to the G.711 standard or coded / decoded according to the standard. G.722.
  • step S4 when the signal is received in successive blocks (or frames marked TRi in step S1), it is estimated (step S4) a quantization noise level specific to the chosen model.
  • a quantization noise level specific to the chosen model.
  • This RSB information depends on the decoded signal S * , but also the type of coding implemented.
  • prior knowledge of the coding by obtaining the information INF allows, together with certain statistical characteristics of the signal S * , to estimate here the signal-to-noise ratio RSB.
  • This step S4 therefore requires knowing a priori the type of encoder that has been used, information that can be obtained for example during a declaration procedure of the encoder called "encoder transaction", which is supposed to be acquired.
  • the type of encoder, the characteristics of its compression model and its quantizer Q make it possible to estimate an evolution of the signal-to-quantization noise ratio, as a function of certain statistical parameters of the signal, for example its variance, its spectral density of power, or others.
  • This relationship between the signal-to-quantization noise ratio and the statistical parameters of the signal involves coder-specific laws which will be described later, for some exemplary embodiments.
  • the necessary statistical parameters can be calculated by classical quantity estimators (eg variance). Based on these estimates, an estimate of the signal to noise quantization ratio can be extrapolated.
  • the estimates can be made indifferently in the time domain, frequency, or any other time-frequency domain (wavelet for example).
  • next step S5 consists in calculating the filter parameters for the reduction of the quantization noise in the received signal S * .
  • Knowledge of the signal-to-noise ratio makes it possible to deduce the expression of a quantization noise reduction filter, this filter being hereinafter called "post-filter” (downstream of the decoder). It is indeed possible to deduce the expression of a digital filter whose purpose is to reduce a noise whose most characteristics are known a priori (its power spectral density for example) and whose level is determined from the estimation of the quantization signal-to-noise ratio obtained at step previous S4.
  • the calculation of the filter can be carried out in the frequency domain and implement any short-term spectral attenuation technique (a spectral subtraction, a Wiener filter, or other).
  • the calculation of the post-filter in step S5 can be performed in the time domain, frequency domain, or any other time-frequency domain.
  • step S6 itself, here amounts to filtering the decoded signal S * by the post-filter calculated in step S5.
  • This step S6 can be performed in the time or frequency domain, according to the constraints related to the implementation and the estimation domain of the PAR parameters and the RSB ratio in the previous steps.
  • a TRi 'frame processed by denoising the quantization noise in step S7 is obtained.
  • RSB quantization signal-to-noise ratio
  • Expression (1) is strongly dependent on the value of this parameter ⁇ .
  • ⁇ the maximum signal-to-noise ratio is obtained for a full-scale signal and decreases rapidly if the signal amplitude decreases.
  • the first variation of the compression law (0 ⁇
  • the implementation of the quantization noise reduction processing is based on the exploitation of this information a priori. In particular, it requires an estimation of the load factor ⁇ , the parameter on which the power of the quantization noise depends, as follows.
  • a variant of the treatment presented here is to reduce the quantization noise, sample by sample, rather than a treatment by successive blocks.
  • the load factor is directly given by the amplitude level of the sample (inverse of the square root of the amplitude) and the continuation of the treatment is similar to that presented above.
  • the ITU-T G.722 coding standardized in 1988 for 64 kbit / s digital audio conferencing applications, is still very widely used. It is a hierarchical coding / decoding at three rates: 64, 56 and 48 kbit / s.
  • the signal is divided into two subbands by a filter called QMF (for "Quadrature Mirror Filter”).
  • QMF for "Quadrature Mirror Filter”
  • ADPCM encoder for "Adaptive Differential Pulse Code Modulation"
  • the high band is coded on 2 bits per sample.
  • the difference between the three bit rates comes from the low band which is coded on 6 bits per sample for the highest bitrate, but it is possible to reserve the last or the last two bits for data transmission.
  • the quality of the higher bit rate is very good, but the coding noise becomes very audible and annoying for the lowest bit rate at 48 kbit / s.
  • the quantization noise reduction processing in the sense of the invention can be advantageously applied in this case.
  • the quantization noise spectrum (solid line curve) is always flat, regardless of the signal spectrum (dotted line curve).
  • the signal to quantization noise ratio depends on the average signal strength and its nature.
  • the RSB ratio correlates well with the average power of the signal S * .
  • the RSB ratio was estimated on segments of 80 samples (5 ms for a sampling frequency of 16 kHz).
  • the representation in the form of point clouds of the figure 8 illustrates even better the correlation between the average power of the signal (abscissa axis) and the signal-to-quantization noise ratio (y-axis), calculated by segments of 80 samples.
  • the figure 9 represents in black on a gray background the areas of the signal where the estimation error of the RSB ratio is greater than 6 dB, and the RSB ratio itself is less than 25 dB, that is to say the signal areas wherein the estimator underestimates the quantization noise, resulting in a lower efficiency of the quantization noise reduction processing. It can nevertheless be noted that these zones correspond to unvoiced signal segments, for which the quantization noise is less troublesome because of the intrinsically noisy nature of the signal.
  • the dashed line represents the estimate of the noise power.
  • the dashed lines delimit the area where the error of the estimate is less than 6 dB. Below the solid line, the RSB is greater than 25 dB.
  • the black dots correspond to the black segments of the figure 9 .
  • a very simple estimate of the RSB ratio based solely on the energy of the decoded signal can give good results for ADPCM type coding / decoding.
  • the estimation of the RSB ratio can be further refined by taking into account, for example, the prediction gain of the ARMA (autoregressive) filters which intervene in the G.722 decoder.
  • the quantization noise reduction process of the invention can be effectively applied for this type of coding / decoding.
  • This example is obviously valid for other types of coding / decoding of the same family as those standardized G.726 or G.727.
  • an advantageous application of the invention can for example aim to reduce the quantization noise of a standardized ITU-G.711 encoder by using the properties of the quantization law implemented. , especially according to law A in Europe. Indeed, in this application, the quantization noise is white and it is possible to estimate the quantization signal-to-noise ratio and hence a gain function that makes it possible to reduce this noise.
  • An advantageous application of the invention thus aims at the reduction of quantization noise in the processing at the extended band extension of the G.711 coder (ITU-T SG16, G.711WB).
  • the invention applies to any type of coding / decoding as long as its intrinsic characteristics are known.

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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)
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Claims (8)

  1. Verfahren zur Verarbeitung eines audiodigitalen Signals, wobei das Signal:
    - gemäß einer vorbestimmten Codierungsart unter Anwendung eines Quantisierungsvorgangs kompressionscodiert (COD) wurde,
    - dann decodiert wurde (DEC),
    wobei das Verarbeitungsverfahren aufweist:
    - eine Schätzung (S4) eines durch die Kompressionscodierung eingeführten Quantisierungsrauschens ausgehend von Informationen (INF), die a priori über die Kompressionscodierungsart erhalten werden, und
    - eine Bestimmung (S5) einer an das decodierte Signal anzuwendenden Filterfunktion, um eine Verarbeitung der Verringerung des geschätzten Quantisierungsrauschens (TBQ) anzuwenden (S6),
    und dadurch gekennzeichnet ist, dass:
    - ausgehend von den Informationen (INF) eine Änderung (Fig.4) des Quantisierungsrauschens (RSB) abhängig von mindestens einem Parameter bezüglich eines Lastparameters (Γ) des decodierten Signals geschätzt wird, und
    - abhängig von einem laufenden Wert des Parameters (Γ) im decodierten Signal (S52, S53) das Quantisierungsrauschen geschätzt wird (S55; S56), um die Filterfunktion zu bestimmen (S57), die an das decodierte Signal mit dem laufenden Parameterwert (Γ) anzuwenden ist (S58).
  2. Verfahren nach Anspruch 1, dadurch gekennzeichnet, dass von den a-priori-Informationen ein Änderungsmodell (Fig.4) eines Signal-Quantisierungsrauschen-Verhältnisses (RSB) abhängig vom Parameter (Γ) des decodiertem Signals abgeleitet wird.
  3. Verfahren nach Anspruch 2, dadurch gekennzeichnet, dass eine Spektralfärbung des Quantisierungsrauschens von den a-priori-Informationen abgeleitet und außerdem die Spektralfärbung berücksichtigt wird, um die an das decodierte Signal anzuwendende Filterfunktion zu bestimmen.
  4. Verfahren nach einem der Ansprüche 1 bis 3, dadurch gekennzeichnet, dass die a-priori-Informationen bei einem Deklarationsverfahren des Codierers erhalten werden.
  5. Verfahren nach einem der Ansprüche 1 bis 4, dadurch gekennzeichnet, dass die Art der Kompressionscodierung eine Codierung gemäß der Norm G.711 ist.
  6. Vorrichtung (TBQ) zur Verarbeitung eines anfangs gemäß einer vorbestimmten Codierungsart kompressionscodierten und dann decodierten audiodigitalen Signals, wobei die Verarbeitungsvorrichtung (TBQ) aufweist:
    - Einrichtungen zum Schätzen eines Quantisierungsrauschens (BQ), das durch die Kompressionscodierung eingeführt wird, ausgehend von dem decodierten Signal und von Informationen (INF), die a priori über die Art der Kompressionscodierung erhalten wurden, und
    - Einrichtungen zur Bestimmung einer an das decodierte Signal anzuwendenden Filterfunktion, um eine Verarbeitung der Verringerung des geschätzten Quantisierungsrauschens (FIL) anzuwenden (S6),
    und dadurch gekennzeichnet ist, dass die Schätzeinrichtungen schätzen:
    - ausgehend von den Informationen (INF) eine Änderung (Fig.4) des Quantisierungsrauschens (RSB) abhängig von mindestens einem Parameter bezüglich eines Lastparameters (Γ) des decodierten Signals, und
    - abhängig von einem laufenden Wert des Parameters (Γ) im decodierten Signal (S52, S53), das Quantisierungsrauschen, um die an das decodierte Signal mit dem laufenden Parameterwert (Γ) anzuwendende (S58) Filterfunktion zu bestimmen (S57).
  7. Vorrichtung nach Anspruch 6, dadurch gekennzeichnet, dass sie in einen Decodierer hinter einer Decodiereinheit (DEC) integriert ist.
  8. EDV-Programm, das dazu bestimmt ist, im Speicher einer Vorrichtung (TBQ) zur Verarbeitung eines anfangs gemäß einer vorbestimmten Codierungsart kompressionscodierten und dann decodierten audiodigitalen Signals gespeichert zu werden, dadurch gekennzeichnet, dass es Anweisungen aufweist, die für die Durchführung des Verfahrens nach einem der Ansprüche 1 bis 5 geeignet sind, wenn diese Anweisungen von einem Prozessor der Verarbeitungsvorrichtung ausgeführt werden.
EP08805992A 2007-06-14 2008-06-13 Nachbearbeitung zur reduzierung des quantifizierungsrauschens eines codierers während der decodierung Active EP2153438B1 (de)

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FR0704242 2007-06-14
PCT/FR2008/051057 WO2009004225A1 (fr) 2007-06-14 2008-06-13 Post-traitement de reduction du bruit de quantification d'un codeur, au decodage

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US (1) US8175145B2 (de)
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JP5898515B2 (ja) * 2012-02-15 2016-04-06 ルネサスエレクトロニクス株式会社 半導体装置及び音声通信装置
CN111179954B (zh) * 2013-03-04 2024-03-12 声代Evs有限公司 用于降低时域解码器中的量化噪声的装置和方法
FR3007184A1 (fr) * 2013-06-14 2014-12-19 France Telecom Controle du traitement d'attenuation d'un bruit de quantification introduit par un codage en compresssion
JP5816992B2 (ja) * 2013-10-31 2015-11-18 株式会社アクセル フィルタの設計方法及びそのフィルタを備えた音響再生装置
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ATE531038T1 (de) 2011-11-15
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EP2153438A1 (de) 2010-02-17
US20100183067A1 (en) 2010-07-22
JP2010529511A (ja) 2010-08-26
ES2376178T3 (es) 2012-03-09
JP5881791B2 (ja) 2016-03-09
JP2015007805A (ja) 2015-01-15

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