EP1435089A1 - Method and system for reducing a voice signal noise - Google Patents

Method and system for reducing a voice signal noise

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Publication number
EP1435089A1
EP1435089A1 EP02776772A EP02776772A EP1435089A1 EP 1435089 A1 EP1435089 A1 EP 1435089A1 EP 02776772 A EP02776772 A EP 02776772A EP 02776772 A EP02776772 A EP 02776772A EP 1435089 A1 EP1435089 A1 EP 1435089A1
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EP
European Patent Office
Prior art keywords
frequency
weighting factor
multiplied
frequency component
calculated
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.)
Granted
Application number
EP02776772A
Other languages
German (de)
French (fr)
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EP1435089B1 (en
Inventor
Marc Ihle
Frank Walter
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BenQ Corp
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Siemens AG
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Classifications

    • 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 invention relates to a method and arrangement for speech processing, in particular of a disturbed snapsig ⁇ Nals.
  • An essential part of speech processing consists in estimating the interference signal or interference noise with which a speech signal recorded by a microphone, for example, is usually afflicted and, if necessary, suppressing it in the input signal in order to transmit only the speech signal if possible.
  • noise suppression undesired artifacts, also called musical tones, often result in the background signal.
  • the invention has for its object to provide a technical teaching for language processing, which enables the transmission of speech with a low data rate and high quality.
  • the invention is therefore initially based on the idea that the frequency components of a speech signal with an interference signal are encoded by a low-rate one Multiplying speech codec ewichtungs tileen by chronologically modifiable frequency-dependent G, wherein a frequency ⁇ component with a current weighting factor multiplied ⁇ is sheet if this is smaller than the last calculated for this frequency component weighting factor, and where a frequency component with the last ⁇ component for this frequency calculated Weighting factor is multiplied if it is smaller than the current weighting factor.
  • a low-rate speech codec is understood in particular to mean a speech codec that delivers a data rate that is less than 5 kbit per second.
  • the interference signal applied to a speech signal is damped in such a way that speech with good quality can be transmitted with little computation or storage effort.
  • the invention is initially based on the knowledge that when using low-rate speech codecs, good speech quality can only be achieved if the artifacts - already explained above - are avoided or reduced as far as possible. This could be recognized by the use of complex simulation tools specially created for this purpose.
  • the invention is based on the knowledge that - as also complex simulations showed - artifacts in the background signal, in particular during speech pauses, are reduced by the special use of current or most recently calculated weighting factors.
  • Figure 1 simplified block diagram of a method for speech processing
  • FIG. 2 flow diagram of a method for noise suppression
  • FIG. 3 simplified block diagram of an arrangement for speech processing.
  • Figure 1 shows a block diagram of a method for speech processing. This process can be roughly divided into the interacting blocks noise suppression and downstream low-rate speech codec NSC.
  • a low-rate speech codec which, for example, delivers a data rate of 4 kbit per second, is known as such, which is why it is not discussed in more detail here.
  • the process for noise suppression can be divided into several function blocks, which are explained below.
  • the block analysis AN and synthesis SY form the framework of the method for noise suppression.
  • a segmentation (not shown in the figure) of the input signal before an analysis AN and the block sizes used are matched to the low-rate speech codec in such a way that the d remains as low as possible urch the Storgerauschunter horrung caused algorithmic delay of the signal.
  • the segmentation of the input signal x (k) takes place, for example, in blocks of 20 ms at a sampling rate of 8 kHz.
  • the processed data can also be passed on to the speech codec in segments with the specified block length.
  • the analysis AN can include a windowing, zero padding and a transformation into the frequency range by means of a Fourier transformation, and the synthesis SY a reverse transformation by an inverse Fourier transformation, the time range and a signal reconstruction according to the overlap add method.
  • the frequency components resulting from the analysis AN have a real and an imaginary part or a magnitude and phase.
  • the magnitudes of different frequency components lying next to one another are initially combined into frequency groups to reduce expenditure, for example on the basis of a bar chart. FGZU1.
  • An amplification calculation VB is carried out for each frequency group on the basis of an a priori and an a posteriori signal-to-noise ratio, which results in weighting factors for the magnitudes of the individual frequency groups.
  • the a priori signal-to-noise behavior is can be derived from the power density spectrum of the disturbed input signal and the a priori noise estimate GS.
  • the A-postio rio signal-to-noise ratio can be calculated from the power density spectrum of the disturbed input signal and the output signal of a buffering P, which in turn is supplied by corrected frequency components summarized by a frequency group summary FGZU2.
  • the power density of the background noise is essentially estimated from the input signal.
  • the a priori noise estimation, the gain calculation, the buffering of the signal magnitude modified for interference signal suppression and the minimum filter are only carried out in a few sub-bands.
  • the magnitude of the input signal transformed into the frequency range and of the signal modified for interference signal suppression are summarized in two bands for frequency group summarization.
  • the width of the sub-bands is based on the Bark scale and therefore varies with the frequency.
  • the output signal of each frequency group of the minimum filter is distributed to the corresponding frequency components or Fourier coefficients by the block frequency group decomposition.
  • the magnitude of the input signal combined in frequency groups can also be multiplied element by element with the output signal of the minimum filter.
  • an a posteriori estimate of the speech signal component is made.
  • the signal of the magnitude values modified for noise reduction combined in frequency groups is stored in the buffering block.
  • the output signals of the a priori noise estimation and the buffering are used in addition to the magnitude values of the n frequency group combined input signal to calculate the gain calculation.
  • the reinforcement calculation results in weighting factors that are l purged - minimum filters are fed.
  • the minimum filter finally determines provided for the multiplication with the frequency components of the frequency groups Ge ⁇ weighting factors.
  • FIG. 1 A Nhand a in Figure 2 flowchart shown a simplified embodiment for Storgerauschunter ⁇ will now be explained in more detail druckung a speech signal.
  • the blocks frequency group summary FGZU1, FGZU2 and frequency group decomposition shown in FIG. 1 are not used.
  • Interfered speech signals recorded by a microphone are converted by a scanning device and a downstream analog-digital conversion into an incoming digital speech signal s (k) which is subject to interference n (k).
  • This input signal is segmented (101) into blocks (block, m) in time, and the blocks (block, m) are mapped in chronological order by transformation into the frequency domain on I frequency components f (i, m) (102), where m represents time and i represents frequency. This can be done, for example, by a Fourier transformation. If the Fourier coefficients of the input signal are designated X (i, m), then the values
  • the frequency components of a speech signal f (i, m) are multiplied by a weighting factor H (i, m) after the segmentation 101 and transformation into the frequency range 102 explained above, the weighting factor being derived, for example, from the estimated a priori and a posteriori already explained above
  • Signal-to-noise ratios can be derived.
  • the a priori signal-to-noise ratio can be derived from the power density spectrum of the disturbed input signal and the a priori noise estimate.
  • the A-posteriori signal-to-noise ratio can be determined from the power t spectrum of the disturbed input signal and the output signal of the buffering can be calculated.
  • the weighting factor which is dependent on the frequency or frequency components, is time-variable and is continuously determined in accordance with the time-varying frequency components.
  • the weighting factor H ( ⁇ , m) currently calculated for this frequency component is not always used to implement a minimum filter for multiplication by a frequency component f ( ⁇ , m), but then , if the last weighting factor H ( ⁇ , m-1) calculated for this frequency component in the previous step is smaller than the current weighting factor, the last weighting factor H ( ⁇ , ml) calculated for this frequency component in this previous step. is used.
  • An embodiment variant of the invention provides that a frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor is above a threshold value, even if the weighting factor last calculated for this frequency component is smaller than the current weighting factor.
  • FIG. 4 shows a program-controlled processor device PE, such as a microcontroller, which can also include a processor CPU and a memory device SPE. Components may be arranged, which - depending on the embodiment can thereby within or au ⁇ ßer Halb said processor means further PE - controlling the processor means associated ⁇ , belonging to the processor means, controlled by the processor means or the processor means
  • the different components can exchange data with the processor device PE via a bus system BUS or input / output interfaces IOS and possibly suitable controllers (not shown).
  • the processor device PE can be part of an electronic device, such as a communication terminal, or a cell phone, and can also control other methods and applications specific to the electronic device.
  • the storage device SPE which can also be one or more volatile or non-volatile RAM or ROM memory modules, or parts of the storage device SPE can be implemented as part of the processor device (shown in the figure) or as an external storage device (Not shown in the figure), which is located outside the processor device PE or even outside the device containing the processor device PE and is connected to the processor device PE by lines or a bus system.
  • the program data which are used to control the device and the method for speech processing and for interference signal suppression are stored in the storage device SPE. It is within the scope of professional action to implement the above-mentioned functional components using program-controlled processors or microcircuits specially provided for this purpose.
  • the digital voice signals, which are subject to interference can be fed to the processor device PE via the input / output interface IOS.
  • a digital signal processor DSP can be provided in order to carry out the steps of the methods explained above in whole or in part.

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

Abstract

The invention concerns a method whereby, before being subjected to a low rate voice coding, an incoming digital voice signal s(k) is chronologically segmented (101) into blocks (block, m) said blocks (block, m) are broken down (102) respectively, in chronological order, into frequency components f(i, m) by a transformation in the frequency range and said frequency components are multiplied by weight factors depending on the frequency and modifiable in time, a frequency component being multiplied by the last weight factor calculated for said frequency component if said factor is less than the current weight factor.

Description

Beschreibungdescription
VERFAHREN UND ANORDNUNG ZUR RAUSCHUNTERDRUCKUNG EINES SPRACHSIGNALSMETHOD AND ARRANGEMENT FOR NOISE REDUCTION OF A VOICE SIGNAL
Die Erfindung betrifft ein Verfahren und eine Anordnung zur Sprachverarbeitung, insbesondere eines gestörten Sprachsig¬ nals .The invention relates to a method and arrangement for speech processing, in particular of a disturbed Sprachsig ¬ Nals.
Die rasante technische Entwicklung im Bereich der Mobilkom u- nikation hat in den letzten Jahren zu ständig erhöhten Anforderungen an die Sprachverarbeitung, insbesondere die Sprachcodierung und die Störgeräuschunterdrückung geführt, was nicht zuletzt auf eine zunehmende Verknappung an Bandbreite und ständig wachsende Anforderungen an die Sprachqualität zu- rückzuführen ist.The rapid technical development in the field of mobile communication has led to constantly increasing demands on speech processing, in particular speech coding and noise suppression, which not least due to an increasing shortage of bandwidth and ever increasing demands on speech quality. is to be returned.
Ein wesentlicher Bestandteil der Sprachverarbeitung besteht darin, das Störsignal bzw. Störgeräusch, mit dem ein beispielsweise durch ein Mikrofon aufgenommenes Sprachsignal üb- licherweise behaftet ist, zu schätzen und gegebenenfalls im Eingangssignal zu unterdrücken, um möglichst nur das Sprachsignal zu übertragen. Allerdings ergeben sich bei gängigen Verfahren zur Störgeräuschunterdrückung häufig unerwünschte Artefakte, auch musical tones genannt, im Hintergrundsignal.An essential part of speech processing consists in estimating the interference signal or interference noise with which a speech signal recorded by a microphone, for example, is usually afflicted and, if necessary, suppressing it in the input signal in order to transmit only the speech signal if possible. However, with common methods for noise suppression, undesired artifacts, also called musical tones, often result in the background signal.
Der Erfindung liegt die Aufgabe zugrunde, eine technische Lehre zur Sprachverarbeitung anzugeben, welche eine Übertragung von Sprache mit niedriger Datenrate und hoher Qualität ermöglicht .The invention has for its object to provide a technical teaching for language processing, which enables the transmission of speech with a low data rate and high quality.
Diese Aufgabe wird durch die Merkmale der unabhängigen Ansprüche gelöst. Vorteilhafte und zweckmäßige Weiterbildungen ergeben sich aus den abhängigen Ansprüchen.This object is solved by the features of the independent claims. Advantageous and expedient further developments result from the dependent claims.
Die Erfindung beruht demnach zunächst auf dem Gedanken, die Frequenzkomponenten eines mit einem Störsignal behafteten Sprachsignals vor einer Codierung durch einen niederratigen Sprachcodec mit zeitlich veränderlichen frequenzabhängigen Gewichtungsfaktoren zu multiplizieren, wobei eine Frequenz¬ komponente mit einem aktuellen Gewichtungsfaktor multipli¬ ziert wird, wenn dieser kleiner ist als der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor, und wobei eine Frequenzkomponente mit dem zuletzt für diese Frequenz¬ komponente berechneten Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist, als der aktuelle Gewichtungsfaktor. Unter einem niederratigen Sprachcodec versteht man dabei ins- besondere einen Sprachcodec, der eine Datenrate, die kleiner als 5 kBit pro Sekunde ist, liefert.The invention is therefore initially based on the idea that the frequency components of a speech signal with an interference signal are encoded by a low-rate one Multiplying speech codec ewichtungsfaktoren by chronologically modifiable frequency-dependent G, wherein a frequency ¬ component with a current weighting factor multiplied ¬ is sheet if this is smaller than the last calculated for this frequency component weighting factor, and where a frequency component with the last ¬ component for this frequency calculated Weighting factor is multiplied if it is smaller than the current weighting factor. A low-rate speech codec is understood in particular to mean a speech codec that delivers a data rate that is less than 5 kbit per second.
Dadurch wird erreicht, dass das einem Sprachsignal beaufschlagte Störsignal so gedämpft wird, dass bei geringem Re- chen- oder Speicheraufwand Sprache mit guter Qualität übertragen werden kann.It is thereby achieved that the interference signal applied to a speech signal is damped in such a way that speech with good quality can be transmitted with little computation or storage effort.
Die Erfindung beruht dabei zunächst auf der Erkenntnis, dass beim Einsatz niederratiger Sprachcodecs nur dann eine gute Sprachqualität erzielt werden kann, wenn die - oben bereits erläuterten - Artefakte möglichst vermieden oder reduziert werden. Dies konnte durch den Einsatz aufwendiger eigens für diesen Zweck erstellter Simulationswerkzeuge erkannt werden.The invention is initially based on the knowledge that when using low-rate speech codecs, good speech quality can only be achieved if the artifacts - already explained above - are avoided or reduced as far as possible. This could be recognized by the use of complex simulation tools specially created for this purpose.
Ferner basiert die Erfindung auf der Erkenntnis, dass - wie ebenfalls aufwendige Simulationen zeigten - durch die spezielle Verwendung aktueller bzw. zuletzt berechneter Gewichtungsfaktoren Artefakte im Hintergrundsignal, insbesondere während Sprachpausen, reduziert werden.Furthermore, the invention is based on the knowledge that - as also complex simulations showed - artifacts in the background signal, in particular during speech pauses, are reduced by the special use of current or most recently calculated weighting factors.
Diese vorteilhafte Wirkung der Erfindung, also der Kombination eines speziellen Verfahrens zur Störgeräuschunterdrückung mit einem niederratigen Sprachcodec, der insbesondere eine Datenrate, die zwischen 3 kBit pro Sekunde und 5 kBit pro Se- künde liegt, liefert, wurde schließlich ebenfalls durch umfangreiche Simulationen bestätigt. Die in weiteren oder abhangigen Ansprüchen beschriebenen Wei¬ terbildungen, Ausgestaltungen und Ausfuhrungsvarianten sind sowohl in Kombination mit den Verfahren als auch in Kombina¬ tion mit den Anordnungen in der Erfindung enthalten.This advantageous effect of the invention, ie the combination of a special method for noise suppression with a low-rate speech codec, which in particular delivers a data rate that is between 3 kbit per second and 5 kbit per second, was finally also confirmed by extensive simulations. The Wei ¬ ter b il d Ungen described in further dependent claims or, A usgestaltungen and variants may be both in combination with the process as well as in Kombina ¬ tion with the arrangements included in this invention.
Die Erfindung wird im folgenden anhand bevorzugter Ausfuh- rungsbeispiele naher beschrieben, wobei die darin enthaltenen Merkmale auch in anderen Kombinationen durch die Erfindung umfasst sein können. Zur Erläuterung dieser Ausfuhrungsbei- spiele sollen nachstehend aufgelistete Figuren dienen:The invention is described in more detail below on the basis of preferred exemplary embodiments, the features contained therein also being able to be included in other combinations by the invention. The figures listed below are intended to explain these exemplary embodiments:
Figur 1 vereinfachtes Blockschaltbild eines Verfahrens zur Sprachverarbeitung;Figure 1 simplified block diagram of a method for speech processing;
Figur 2 Flussdiagramm eines Verfahrens zur Storgerauschunterdruckung;FIG. 2 flow diagram of a method for noise suppression;
Figur 3 vereinfachtes Blockschaltbild einer Anordnung zur Sprachverarbeitung .Figure 3 simplified block diagram of an arrangement for speech processing.
Figur 1 zeigt ein Blockschaltbild eines Verfahrens zur Sprachverarbeitung. Dieses Verfahren lasst sich grob in die zusammenwirkenden Blocke Storgerauschunterdruckung und nachgeschalteter niederratiger Sprachcodec NSC aufteilen. Ein niederratiger Sprachcodec, der beispielsweise eine Datenrate von 4 kBit pro Sekunde liefert, ist als solcher bekannt, weshalb an dieser Stelle nicht naher darauf eingegangen wird.Figure 1 shows a block diagram of a method for speech processing. This process can be roughly divided into the interacting blocks noise suppression and downstream low-rate speech codec NSC. A low-rate speech codec, which, for example, delivers a data rate of 4 kbit per second, is known as such, which is why it is not discussed in more detail here.
Das Verfahren zur Storgerauschunterdruckung kann in mehrere Funktionsblocke unterteilt werden, die im folgenden erläutert werden.The process for noise suppression can be divided into several function blocks, which are explained below.
Die Blocke Analyse AN und Synthese SY bilden den Rahmen des Verfahrens zur Gerauschunterdruckung. Eine vor einer Analyse AN stattfindende Segmentierung (in Figur nicht dargestellt) des Eingangssignals, sowie die verwendeten Blockgroßen sind auf den niederratigen Sprachcodec derart abgestimmt, dass die durch die Storgerauschunterdruckung verursachte algorithmische Verzögerung des Signals möglichst gering bleibt. Die Segmentierung des Eingangssignals x(k) erfolgt beispielsweise in Blocke zu 20ms bei einer Abtastrate von 8kHz. Die Weiter- gäbe der prozessierten Daten an den Sprachcodec kann segmentweise ebenfalls mit der angegebenen Blocklange erfolgen.The block analysis AN and synthesis SY form the framework of the method for noise suppression. A segmentation (not shown in the figure) of the input signal before an analysis AN and the block sizes used are matched to the low-rate speech codec in such a way that the d remains as low as possible urch the Storgerauschunterdruckung caused algorithmic delay of the signal. The segmentation of the input signal x (k) takes place, for example, in blocks of 20 ms at a sampling rate of 8 kHz. The processed data can also be passed on to the speech codec in segments with the specified block length.
Die Analyse AN kann dabei eine Fensterung, Zero-Padding und eine Transformation in den Frequenzbereich durch eine Fou- πertransformation umfassen, und die Synthese SY eine Rucktransformation durch eine inverse Fouriertransformationm den Zeitbereich und eine Signalrekonstruktion nach dem Overlap Add Verfahren.The analysis AN can include a windowing, zero padding and a transformation into the frequency range by means of a Fourier transformation, and the synthesis SY a reverse transformation by an inverse Fourier transformation, the time range and a signal reconstruction according to the overlap add method.
Die aus der Analyse AN hervorgehenden Frequenzkomponenten weisen einen Real- und einen Imagmarteil auf bzw. eine Magnitude und Phase. Die Magnituden verschiedener nebeneinanderliegender Frequenzkomponenten werden zur Aufwandsreduzie- rung beispielsweise anhand einer Barktabelle zunächst zu Fre- quenzgruppen zusammengefasst FGZU1.The frequency components resulting from the analysis AN have a real and an imaginary part or a magnitude and phase. The magnitudes of different frequency components lying next to one another are initially combined into frequency groups to reduce expenditure, for example on the basis of a bar chart. FGZU1.
Für jede Frequenzgruppe wird anhand eines A-priori und eines A-posteriori Signal-zu-Rauschverhaltnisses eine Verstarkungs- berechnung VB durchgeführt, welche Gewichtungsfaktoren für die Magnituden der einzelnen Frequenzgruppen zum Ergebnis hat. Das A-priori Signal-zu-Rauschverhalt is kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und der A-priori Gerauschschatzung GS abgeleitet werden. Das A-poste- rioπ Signal-zu-Rauschverhaltnis kann aus dem Leistungsdich- tespektrum des gestörten Eingangssignals und dem Ausgangssig- nal einer Pufferung P, der wiederum durch eine Frequenzgruppenzusammenfassung FGZU2 zusammengefasste korrigierte Frequenzkomponenten zugeführt werden, berechnet werden.An amplification calculation VB is carried out for each frequency group on the basis of an a priori and an a posteriori signal-to-noise ratio, which results in weighting factors for the magnitudes of the individual frequency groups. The a priori signal-to-noise behavior is can be derived from the power density spectrum of the disturbed input signal and the a priori noise estimate GS. The A-postio rio signal-to-noise ratio can be calculated from the power density spectrum of the disturbed input signal and the output signal of a buffering P, which in turn is supplied by corrected frequency components summarized by a frequency group summary FGZU2.
Vor einer Zerlegung FGZE der zuvor zu Frequenzgruppen zusam- engefassten Frequenzkomponenten und einer Multiplikation der Frequenzkomponenten mit jeweils dem für eine entsprechende Frequenzgruppe berechneten Gewichtungsfaktor zur Storge¬ rauschunterdruckung, werden die Gewichtungsfaktoren einer so¬ genannten Minimum-Filterung MF unterzogen, welche spater an¬ hand Figur 2 naher erläutert wird.Before decomposing FGZE of the frequency components previously combined into frequency groups and multiplying the frequency components by that for a corresponding one Frequency group calculated weighting factor to the storge ¬ noise reduction, the weighting factors of said minimum so ¬ filtering MF are subjected, which later is to hand ¬ figure 2 near explained.
Zur Storgerauschschatzung erfolgt also im wesentlichen eine Schätzung der Leistungsdichte des Hintergrundgeräusches aus dem Eingangssignal. Zur Reduktion der benotigten Rechenleis- tung sowie des Speicherverbrauchs werden die A-priori Ge- rauschschatzung, die Verstarkungsberechnung, die Pufferung der zur Storsignalunterdruckung modif zierten Signalmagnitude und das Minimum-Filter nur in wenigen Teilbandern durchgeführt. Hierzu werden die Magnitude des in den Frequenzbereich transformierten Eingangssignals und des zur Storsignalunter- druckung modifizierten Signals mit zwei Blocken zur Frequenzgruppen-Zusammenfassung in Teilbander zusammengefasst . Die Breite der Teilbander orientiert sich dabei an der Bark-Skala und variiert daher mit der Frequenz. Das Ausgangssignal jeder Frequenzgruppe des Minimum-Filters wird durch den Block Fre- quenzgruppen-Zerlegung auf die entsprechenden Frequenzkomponenten bzw. Fourier-Koefflzienten verteilt. Zur Berechnung des Eingangssignals des Pufferungs-Blocks kann in einer anderen Ausfuhrungsvariante anstelle einer Frequenzgruppen- Zusammenfassung des zur Storsignalunterdruckung modifizierten Signals, auch die in Frequenzgruppen zusammengefasste Magnitude des Eingangssignals elementweise mit dem Ausgangssignal des Minimum-Filters multipliziert werden.In order to estimate interference noise, the power density of the background noise is essentially estimated from the input signal. To reduce the required computing power and memory consumption, the a priori noise estimation, the gain calculation, the buffering of the signal magnitude modified for interference signal suppression and the minimum filter are only carried out in a few sub-bands. For this purpose, the magnitude of the input signal transformed into the frequency range and of the signal modified for interference signal suppression are summarized in two bands for frequency group summarization. The width of the sub-bands is based on the Bark scale and therefore varies with the frequency. The output signal of each frequency group of the minimum filter is distributed to the corresponding frequency components or Fourier coefficients by the block frequency group decomposition. To calculate the input signal of the buffering block, in another embodiment variant, instead of a frequency group summary of the signal modified for interference signal suppression, the magnitude of the input signal combined in frequency groups can also be multiplied element by element with the output signal of the minimum filter.
Neben der Storgerauschschatzung erfolgt eine A-posteriori Schätzung des Sprachsignalanteils . Hierzu wird das in Frequenzgruppen zusammengefasste Signal der zur Gerauschreduktion modifizierten Magnitudenwerte im Block Pufferung gespeichert. Die Ausgangssignale der A-priori Gerauschschatzung und der Pufferung dienen neben der Magnitudenwerte des n Fre- quenzgruppen zusammengefassten Eingangssignals zur Berechnung der Verstarkungsberechnung. Aus der Verstarkungsberechnung resultieren Gewichtungsfaktoren, die einem - unten naher er- läuterten - Minimum-Filter zugeführt werden. Das Minimum- Filter ermittelt schließlich die für die Multiplikation mit den Frequenzkomponenten der Frequenzgruppen vorgesehenen Ge¬ wichtungsfaktoren .In addition to the noise estimate, an a posteriori estimate of the speech signal component is made. For this purpose, the signal of the magnitude values modified for noise reduction combined in frequency groups is stored in the buffering block. The output signals of the a priori noise estimation and the buffering are used in addition to the magnitude values of the n frequency group combined input signal to calculate the gain calculation. The reinforcement calculation results in weighting factors that are l purged - minimum filters are fed. The minimum filter finally determines provided for the multiplication with the frequency components of the frequency groups Ge ¬ weighting factors.
Anhand eines in Figur 2 dargestellten Flussdiagramms wird nun eine vereinfachte Ausführungsvariante zur Storgerauschunter¬ druckung eines Sprachsignals näher erläutert. Dabei kommen die in Figur 1 dargestellten Blöcke Frequenzgruppenzusammen- fassung FGZUl, FGZU2 und Frequenzgruppenzerlegung nicht zum Einsatz . A Nhand a in Figure 2 flowchart shown a simplified embodiment for Storgerauschunter ¬ will now be explained in more detail druckung a speech signal. The blocks frequency group summary FGZU1, FGZU2 and frequency group decomposition shown in FIG. 1 are not used.
Durch ein Mikrofon aufgenommene gestörte Sprachsignale werden durch eine Abtasteinrichtung und eine nachgeschaltete Analog- Digital-Wandlung in ein eingehendes mit Störungen n(k) behaftetes digitales Sprachsignal s(k) umgesetzt. Dieses Eingangssignal wird zeitlich in Blöcke (block, m) segmentiert (101), und die Blöcke (block, m) in zeitlicher Reihenfolge durch eine Transformation in den Frequenzbereich jeweils auf I Frequenz- komponenten f(i,m) abgebildet (102), wobei m die Zeit und i die Frequenz repräsentieren. Dies kann beispielsweise durch eine Fouriertransformation erfolgen. Werden die Fourier- Koeffizienten des Eingangssignals mit X(i,m) bezeichnet, so können die Werte |X(i,m) | Λ2 als Frequenzkomponenten bezeich- net werden.Interfered speech signals recorded by a microphone are converted by a scanning device and a downstream analog-digital conversion into an incoming digital speech signal s (k) which is subject to interference n (k). This input signal is segmented (101) into blocks (block, m) in time, and the blocks (block, m) are mapped in chronological order by transformation into the frequency domain on I frequency components f (i, m) (102), where m represents time and i represents frequency. This can be done, for example, by a Fourier transformation. If the Fourier coefficients of the input signal are designated X (i, m), then the values | X (i, m) | Λ 2 are called frequency components.
Die Frequenzkomponenten eines Sprachsignals f(i,m) werden nach oben erläuterter Segmentierung 101 und Transformation in den Frequenzbereich 102 mit einem Gewichtungsfaktor H(i,m) multipliziert, wobei der Gewichtungsfaktor beispielsweise aus den oben bereits erläuterten geschätzten A-priori und A- posteriori Signal-zu-Rauschverhältnissen abgeleitet werden kann. Das A-priori Signal-zu-Rauschverhaltnis kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und der A-priori Geräuschschätzung abgeleitet werden. Das A-poste- riori Signal-zu Rauschverhältnis kann aus dem Leistungsdich- tespektrum des gestörten Eingangssignals und dem Ausgangssig- nal der Pufferung berechnet werden.The frequency components of a speech signal f (i, m) are multiplied by a weighting factor H (i, m) after the segmentation 101 and transformation into the frequency range 102 explained above, the weighting factor being derived, for example, from the estimated a priori and a posteriori already explained above Signal-to-noise ratios can be derived. The a priori signal-to-noise ratio can be derived from the power density spectrum of the disturbed input signal and the a priori noise estimate. The A-posteriori signal-to-noise ratio can be determined from the power t spectrum of the disturbed input signal and the output signal of the buffering can be calculated.
Der frequenz- oder frequenzkomponentenabhangige Gewichtungs- faktor ist dabei zeitlich veränderlich und wird entsprechend der zeitlich veränderlichen Frequenzkomponenten fortlaufend aktuell ermittelt. Um unerwünschte Artefakte im Hmtergrund- signal zu vermeiden, wird allerdings zur Realisierung eines Minimum-Filters zur Multiplikation mit einer Frequenzkompo- nente f(ι,m) nicht immer der aktuell für diese Frequenzkomponente berechnete Gewichtungsfaktor H(ι,m) herangezogen, sondern dann, wenn der zuletzt, also im vorhergehende Schritt, für diese Frequenzkomponente berechnete Gewichtungsfaktor H(ι,m-1) kleiner ist, als der aktuelle Gewichtungsfaktor, der zuletzt, also im vorhergehende Schritt, für diese Frequenzkomponente berechnete Gewichtungsfaktor H (ι,m-l) herangezogen wird.The weighting factor, which is dependent on the frequency or frequency components, is time-variable and is continuously determined in accordance with the time-varying frequency components. In order to avoid undesired artifacts in the background signal, the weighting factor H (ι, m) currently calculated for this frequency component is not always used to implement a minimum filter for multiplication by a frequency component f (ι, m), but then , if the last weighting factor H (ι, m-1) calculated for this frequency component in the previous step is smaller than the current weighting factor, the last weighting factor H (ι, ml) calculated for this frequency component in this previous step. is used.
Eine Ausfuhrungsvariante der Erfindung sieht vor, dass e ne Frequenzkomponente mit dem aktuellen Gewichtungsfaktor multipliziert wird, wenn der frequenzabhangige Gewichtungsfaktor über einem Schwellwert liegt, auch dann, wenn der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor kleiner ist als der aktuelle Gewichtungsfaktor.An embodiment variant of the invention provides that a frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor is above a threshold value, even if the weighting factor last calculated for this frequency component is smaller than the current weighting factor.
Dies kann durch einen Filter realisiert werden, der den aktuellen Gewichtsfaktor jeweils mit dem zeitlich vorangegangenen Gewichtsfaktor bei der selben Frequenz vergleicht und den kleineren der beiden Werte für die Anwendung auf die Fre- quenzkomponente auswählt. Wird der feste Schwellwert 0.76 durch den aktuellen Gewichtungsfaktor überschritten, so findet keine Modifikation der Frequenzkomponente statt.This can be implemented by means of a filter which compares the current weight factor with the previous weight factor at the same frequency and selects the smaller of the two values for application to the frequency component. If the fixed threshold value 0.76 is exceeded by the current weighting factor, no modification of the frequency component takes place.
Figur 4 zeigt eine programmgesteuerte Prozessoreinrichtung PE wie beispielsweise einen Mikrocontroller, die auch einen Prozessor CPU und eine Speichereinrichtung SPE umfassen kann. Je nach Ausführungsvariante können dabei innerhalb oder au¬ ßerhalb der Prozessoreinrichtung PE weitere - der Prozessor¬ einrichtung zugeordnete, zur Prozessoreinrichtung gehörende, durch die Prozessoreinrichtung gesteuerte oder die Prozessor- einrichtung steuernde - Komponenten angeordnet sein, derenFIG. 4 shows a program-controlled processor device PE, such as a microcontroller, which can also include a processor CPU and a memory device SPE. Components may be arranged, which - depending on the embodiment can thereby within or au ¬ ßerhalb said processor means further PE - controlling the processor means associated ¬, belonging to the processor means, controlled by the processor means or the processor means
Funktion im Zusammenhang mit einer Prozessoreinrichtung einem Fachmann hinreichend bekannt sind, und auf welche daher an dieser Stelle nicht mehr eingegangen wird. Die unterschiedlichen Komponenten können über ein Bussystem BUS oder Ein/Aus- gabeschnittstellen IOS und gegebenenfalls geeignete Controller (nicht dargestellt) mit der Prozessoreinrichtung PE Daten austauschen. Dabei kann die Prozessoreinrichtung PE Bestandteil eines elektronischen Gerätes, wie beispielsweise eines Kommunikationsendgerätes, oder eines Mobiltelefons sein und auch andere für das elektronische Gerät spezifische Verfahren und Anwendungen steuern.Function in connection with a processor device are well known to a person skilled in the art, and which will therefore not be discussed further here. The different components can exchange data with the processor device PE via a bus system BUS or input / output interfaces IOS and possibly suitable controllers (not shown). The processor device PE can be part of an electronic device, such as a communication terminal, or a cell phone, and can also control other methods and applications specific to the electronic device.
Je nach Ausführungsvariante kann die Speichereinrichtung SPE, bei der es sich auch um einen oder mehrere flüchtige oder nicht flüchtige RAM- oder ROM-Speicherbausteine handeln kann, oder Teile der Speichereinrichtung SPE als Teil der Prozessoreinrichtung (in Figur dargestellt) realisiert sein oder als externe Speichereinrichtung (in Figur nicht dargestellt) realisiert sein, die außerhalb der Prozessoreinrichtung PE oder sogar außerhalb des die Prozessoreinrichtung PE beinhaltenden Gerätes lokalisiert ist und durch Leitungen oder ein Bussystem mit der Prozessoreinrichtung PE verbunden ist.Depending on the embodiment variant, the storage device SPE, which can also be one or more volatile or non-volatile RAM or ROM memory modules, or parts of the storage device SPE can be implemented as part of the processor device (shown in the figure) or as an external storage device (Not shown in the figure), which is located outside the processor device PE or even outside the device containing the processor device PE and is connected to the processor device PE by lines or a bus system.
In der Speichereinrichtung SPE sind die Programmdaten, die zur Steuerung des Gerätes und des Verfahrens zur Sprachverarbeitung und zur Störsignalunterdrückung herangezogen werden, abgelegt. Es liegt im Rahmen fachmännischen Handelns, oben erwähnte Funktionskomponenten durch programmgesteuerte Prozessoren oder eigens für diesen Zweck vorgesehene Mikroschal- tungen zu realisieren. Über die Ein/Ausgabeschnittstelle IOS können die mit Störungen behafteten digitalen Sprachsignale der Prozessoreinrichtung PE zugeführt werden. Neben dem Prozessor CPU kann ein digitaler Signalprozessor DSP vorgesehen sein, um die Schritte der oben erläuterten Verfahren ganz oder teilweise auszuführen. The program data which are used to control the device and the method for speech processing and for interference signal suppression are stored in the storage device SPE. It is within the scope of professional action to implement the above-mentioned functional components using program-controlled processors or microcircuits specially provided for this purpose. The digital voice signals, which are subject to interference, can be fed to the processor device PE via the input / output interface IOS. In addition to the processor CPU, a digital signal processor DSP can be provided in order to carry out the steps of the methods explained above in whole or in part.

Claims

Patentansprüche claims
1. Verfahren zur Sprachverarbeitung,1. Language processing method,
- bei dem ein eingehendes digitales Sprachsignal s(k) zeit- lieh m Blocke (block, m) segmentiert wird (101),- in which an incoming digital voice signal s (k) is temporarily lent m blocks (block, m) is segmented (101),
- bei dem die Blocke (block, m) in zeitlicher Reihenfolge durch eine Transformation in den Frequenzbereich jeweils auf Frequenzkomponenten (f,ι) abgebildet werden (102),- in which the blocks (block, m) are mapped (102) in time sequence by a transformation into the frequency range on frequency components (f, ι),
- die Frequenzkomponenten mit zeitlich veränderlichen fre- quenzabhangigen Gewichtungsfaktoren multipliziert werden,- the frequency components are multiplied by time-dependent frequency-dependent weighting factors,
- wobei eine Frequenzkomponente mit dem aktuellen Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist als der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor, - wobei eine Frequenzkomponente mit dem zuletzt für diesea frequency component is multiplied by the current weighting factor if this is smaller than the last weighting factor calculated for this frequency component, and a frequency component is multiplied by the last one for this
Frequenzkomponente berechneten Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist, als der aktuelle Gewichtungsfaktor, undFrequency component calculated weighting factor is multiplied if this is smaller than the current weighting factor, and
- bei dem die derart gewichteten Frequenzkomponenten nach ei- ner Rucktransformation in den Zeitbereich einem niederratigen Sprachcodec zugeführt werden.- in which the frequency components weighted in this way are fed to a low-rate speech codec after a jerk transformation in the time domain.
2. Verfahren nach Anspruch 1, bei dem eine Frequenzkomponente mit dem aktuellen Gewichtungsfaktor multipliziert wird, wenn der frequenzabhangige Gewichtungsfaktor über einem Schwellwert liegt, auch dann, wenn der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor kleiner ist als der aktuelle Gewichtungsfaktor.2. The method of claim 1, in which a frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor is above a threshold value, even if the weighting factor last calculated for this frequency component is smaller than the current weighting factor.
3. Anordnung zur Storgerauschunterdruckung3. Arrangement for noise suppression
- mit einem Eingang (IOS) für digitale Sprachsignale, und- With an input (IOS) for digital voice signals, and
- mit einer Prozessoreinrichtung (PE) , die derart eingerich - With a processor device (PE), which is set up in this way
- ein eingehendes digitales Sprachsignal s(k) zeitlich m Blocke (block, m) segmentiert wird (101), - die Blöcke (block, m) in zeitlicher Reihenfolge durch eine Transformation in den Frequenzbereich jeweils auf Frequenz¬ komponenten (f,i) abgebildet werden (102),an incoming digital speech signal s (k) is segmented in time m blocks (block, m) (101), - the blocks (block, m) (f, i) in chronological order by a transformation in the frequency domain respectively to frequency ¬ components are mapped (102)
- die Frequenzkomponenen mit zeitlich veränderlichen fre- quenzabhängigen Gewichtungsfaktoren multipliziert werden,- the frequency components are multiplied by time-dependent frequency-dependent weighting factors,
- wobei eine Frequenzkomponente mit dem aktuellen Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist, als der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor, und - wobei eine Frequenzkomponente mit dem zuletzt für diese- where a frequency component is multiplied by the current weighting factor if this is smaller than the weighting factor last calculated for this frequency component, and - where a frequency component is multiplied by the last one for this
Frequenzkomponente berechneten Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist, als der aktuelle Gewichtungsfaktor, und daßFrequency component calculated weighting factor is multiplied, if this is smaller than the current weighting factor, and that
- die derart gewichteten Frequenzkomponenten nach einer Rück- transformation in den Zeitbereich einer niederratigen- The frequency components weighted in this way after a re-transformation into the time domain of a low rate
Sprachcodierung unterzogen werden.Undergo speech coding.
4. Anordnung nach Anspruch 3, bei der4. Arrangement according to claim 3, wherein
- eine Frequenzkomponente mit dem aktuellen Gewichtungsfaktor multipliziert wird, wenn der frequenzabhängige Gewichtungsfaktor über einem Schwellwert liegt, auch dann, wenn der zuletzt für diese Frequenzkomponente berechnete Gewichtungsfaktor kleiner ist als der aktuelle Gewichtungsfaktor. - A frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor is above a threshold value, even if the weighting factor last calculated for this frequency component is smaller than the current weighting factor.
EP02776772A 2001-10-12 2002-10-02 Method and system for reducing a voice signal noise Expired - Lifetime EP1435089B1 (en)

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