EP1521243A1 - Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung - Google Patents

Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung Download PDF

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Publication number
EP1521243A1
EP1521243A1 EP03022251A EP03022251A EP1521243A1 EP 1521243 A1 EP1521243 A1 EP 1521243A1 EP 03022251 A EP03022251 A EP 03022251A EP 03022251 A EP03022251 A EP 03022251A EP 1521243 A1 EP1521243 A1 EP 1521243A1
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EP
European Patent Office
Prior art keywords
signal
gain
speech
fixed gain
noise
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP03022251A
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English (en)
French (fr)
Inventor
Christophe Dr. Beaugeant
Nicolas Dütsch
Herbert Dr. Heiss
Hervé Dr. Taddei
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Siemens Corp
Original Assignee
Siemens AG
Siemens Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens AG, Siemens Corp filed Critical Siemens AG
Priority to EP03022251A priority Critical patent/EP1521243A1/de
Priority to PCT/EP2004/051810 priority patent/WO2005031709A1/en
Publication of EP1521243A1 publication Critical patent/EP1521243A1/de
Withdrawn legal-status Critical Current

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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
    • 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
    • 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
    • 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
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G10L2021/02168—Noise filtering characterised by the method used for estimating noise the estimation exclusively taking place during speech pauses

Definitions

  • the invention refers to a speech coding method applying noise reduction
  • noise reduction methods have been developed in speech processing. Most of the methods are performed in the frequency domain. They commonly comprise three major components:
  • the suppression rule modifies only the spectral amplitude, not the phase. It has been shown, that there is no need to modify the phase in speech enhancement processing. Nevertheless, this approximation is only valid for a Signal to Noise Ratio (SNR) greater than 6dB. However, this condition is supposed to be satisfied in the majority of the noise reduction algorithms.
  • SNR Signal to Noise Ratio
  • FIG. 1 A scheme of a treatment of a speech signal with noise reduction is depicted in Fig. 1.
  • the speech component s(p), where p denotes a time interval is superimposed with a noise component n(p).
  • n(p) This results in the total signal y(p).
  • the total signal y(p) undergoes a FFT.
  • the result are Fourier components Y(p, f k ), where f k denotes a quantized frequency.
  • the noise reduction NR is applied, thus producing modified Fouriercomponents S(p, S and (p,f k ). This leads after an IFFT to a clean speech signal estimate s and (p).
  • a problem of any spectral weighting noise reduction method is its computational complexity, e.g. if the following steps have to be performed successively:
  • a method for transmitting speech data said speech data are encoded by using an analysis through synthesis method.
  • a synthesised signal is produced for approximating the original signal.
  • the production of the synthesised signal is performed by using at least a fixed codebook with a respective fixed gain and optionally an adaptive codebook and a adaptive gain. The entries of the codebook and the gain are chosen such, that the synthesised signal resembles the original signal.
  • Parameters describing these quantities will be transmitted from a sender to a receiver, e.g. from a near-end speaker to a far-end speaker or vice versa.
  • the invention is based on the idea of modifying the fixed gain determined for the signal containing a noise component and a speech component. Objective of this modification is to obtain a useful estimate of the fixed gain of the speech component or clean signal.
  • the modification is done by subtraction of an estimate of the fixed gain of the noise component.
  • the fixed gain of the noise component may be derived from an analysis of the power of the signal in a predetermined time window.
  • One advantage of this procedure is its low computational complexity, particularly if the speech enhancement through noise reduction is done independently from an encoding / decoding unit, e.g. in a certain position within a network, where according to a noise reduction method in the time domain all the steps of decoding, FFT, speech enhancement , IFFT and encoding would have to be performed one after the other. This is not necessary for a noise reduction method according based on modification of parameters
  • Another advantage is that by using the parameters for any modification, a repeated encoding and decoding process, the so called “tandeming" can be avoided, because the modification takes place in the parameter itself. Any tandeming decreases the speech quality. Furthermore the delay due to the additional encoding/decoding, which is e.g. in GSM typically 5 ms can be avoided.
  • the procedure is furthermore also applicable within a communications network.
  • An encoding apparatus set up for performing the above described encoding method includes at least a processing unit.
  • the encoding apparatus may be part of a communications device, e.g. a cellular phone or it may be also situated in a communication network or a component thereof.
  • the codec consists of a multi-rate, that is, the AMR codec can switch between the following bit rates: 12.2, 10.2, 7.95, 7.40, 6.70, 5.90, 5.15 and 4.75 kbit/s, speech codec, a source-controlled rate scheme including a Voice Activity Detection (VAD), a comfort noise generation system and an error concealment mechanism to compensate the effects of transmission errors.
  • VAD Voice Activity Detection
  • Fig. 2 shows the scheme of the AMR encoder. It uses a LTP (long term prediction) filter. It is transformed to an equivalent structure called adaptive codebook. This codebook saves former LPC filtered excitation signals. Instead of subtracting a long-term prediction as the LTP filter does, an adaptive codebook search is done to get an excitation vector from further LPC filtered speech samples. The amplitude of this excitation is adjusted by a gain factor g a .
  • the encoder transforms the speech signal to parameters which describe the speech.
  • these parameters namely the LSF (or LPC) coefficients, the lag of the adaptive codebook, the index of the fixed codebook and the codebook gains, as "speech coding parameters”.
  • the domain will be called “(speech) codec parameter domain” and the signals of this domain are subscripted with frame index $k$.
  • Fig. 3 shows the signal flow of the decoder.
  • the decoder receives the speech coding parameters and computes the excitation signal of the synthesis filter.
  • This excitation signal is the sum of the excitations of the fixed and adaptive codebook scaled with their respective gain factors.
  • the speech signal is post-processed.
  • a (total) signal containing clean speech or a speech component and a noise component is encoded.
  • a fixed gain g y (m) of the total signal is calculated.
  • This fixed gain g y (m) of the total signal is subject to a gain modification which bases on a noise gain estimation.
  • an estimate of the fixed gain g and n ( m ) is determined, which is used for the gain modification.
  • the result of the gain modification is an estimate of the fixed gain g and s ( m ) of the clean speech or the speech component.
  • This parameter is transmitted from a sender to a receiver. At the receiver side it is decoded.
  • g s ( m ) g y ( m ) - g n ( m ), where m denotes a time interval, e.g. a frame or a subframe, g and n ( m ) the estimate of the noise component and g and s ( m ) the estimate of the clean codebook gain. It will be described in the next section in reference with a different embodiment, how the estimate of fixed gain g and n ( m ) of the noise component can be calculated.
  • That window of length D is divided in U sub-windows of length V .
  • the minimum value in the window of length D is the minimum of the set of minimums on each subwindow.
  • a buffer, Min_I of U elements contains the set of minimums from the last U sub-windows. It is renewed each time that V values of P are computed. The oldest element of the buffer is deleted and replaced by the minimum of the last V values of P.
  • the minimum on the window of length D, ⁇ and 2 / N for each sub-frame m is the minimum between the minimum of the buffer and the last value of P computed.
  • ⁇ and 2 / N can be increased by a gain parameter omin to compensate the bias of the estimation.
  • a bias might be due to a continued overestimating of the noise, e.g. if a continually present murmuring is considered as noise only.
  • the noise reduction may cause some artefacts during the voice activity periods, e.g. that the speech signal is attenuated due to an overestimation of the noise component

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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)
  • Quality & Reliability (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
EP03022251A 2003-10-01 2003-10-01 Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung Withdrawn EP1521243A1 (de)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP03022251A EP1521243A1 (de) 2003-10-01 2003-10-01 Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung
PCT/EP2004/051810 WO2005031709A1 (en) 2003-10-01 2004-08-17 Speech coding method applying noise reduction by modifying the codebook gain

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP03022251A EP1521243A1 (de) 2003-10-01 2003-10-01 Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung

Publications (1)

Publication Number Publication Date
EP1521243A1 true EP1521243A1 (de) 2005-04-06

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EP03022251A Withdrawn EP1521243A1 (de) 2003-10-01 2003-10-01 Verfahren zur Sprachkodierung mit Geräuschunterdrückung durch Modifizierung der Kodebuchverstärkung

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EP (1) EP1521243A1 (de)
WO (1) WO2005031709A1 (de)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2437172C1 (ru) * 2007-11-04 2011-12-20 Квэлкомм Инкорпорейтед Способ кодирования/декодирования индексов кодовой книги для квантованного спектра мдкп в масштабируемых речевых и аудиокодеках

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3079151A1 (de) 2015-04-09 2016-10-12 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Audiocodierer und verfahren zur codierung eines audiosignals

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020184010A1 (en) * 2001-03-30 2002-12-05 Anders Eriksson Noise suppression
EP1301018A1 (de) * 2001-10-02 2003-04-09 Alcatel Verfahren und Vorrichtung zum Ändern eines digitalen Signals im Kodebereich

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020184010A1 (en) * 2001-03-30 2002-12-05 Anders Eriksson Noise suppression
EP1301018A1 (de) * 2001-10-02 2003-04-09 Alcatel Verfahren und Vorrichtung zum Ändern eines digitalen Signals im Kodebereich

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
CHANDRAN R ET AL: "COMPRESSED DOMAIN NOISE REDUCTION AND ECHO SUPPRESSION FOR NETWORK SPEECH ENHANCEMENT", PROCEEDINGS OF THE 43RD. IEEE MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS. MWSCAS 2000. LANSING, MI. NEW YORK, NY: IEEE, US, vol. 1 OF 3, 8 August 2000 (2000-08-08) - 11 August 2000 (2000-08-11), pages 10 - 13, XP002951730, ISBN: 0-7803-6476-7 *
LIM J S ET AL: "ENHANCEMENT AND BANDWIDTH COMPRESSION OF NOISY SPEECH", PROCEEDINGS OF THE IEEE, IEEE. NEW YORK, US, vol. 67, no. 12, December 1979 (1979-12-01), pages 1586 - 1604, XP000891496, ISSN: 0018-9219 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2437172C1 (ru) * 2007-11-04 2011-12-20 Квэлкомм Инкорпорейтед Способ кодирования/декодирования индексов кодовой книги для квантованного спектра мдкп в масштабируемых речевых и аудиокодеках
US8515767B2 (en) 2007-11-04 2013-08-20 Qualcomm Incorporated Technique for encoding/decoding of codebook indices for quantized MDCT spectrum in scalable speech and audio codecs

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