EP1435089B1 - Method and system for reducing a voice signal noise - Google Patents
Method and system for reducing a voice signal noise Download PDFInfo
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- EP1435089B1 EP1435089B1 EP02776772A EP02776772A EP1435089B1 EP 1435089 B1 EP1435089 B1 EP 1435089B1 EP 02776772 A EP02776772 A EP 02776772A EP 02776772 A EP02776772 A EP 02776772A EP 1435089 B1 EP1435089 B1 EP 1435089B1
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal 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 according to claim 1 and an arrangement according to claim 3 for speech processing, in particular a disturbed speech signal.
- An essential part of the speech processing is to estimate the interference signal or noise with which a voice signal picked up, for example, by a microphone is usually afflicted, and optionally to suppress it in the input signal in order to transmit as possible only the voice signal.
- common methods for noise suppression often result in unwanted artifacts, also called musical tones, in the background signal.
- the invention has for its object to provide a technical teaching for voice processing, which allows a transmission of low-speed voice and high quality.
- the invention is therefore based initially on the idea of the frequency components of a speech signal having an interference signal before coding by a low-rate To multiply speech codec with time-varying frequency-dependent weighting factors, wherein a frequency component is multiplied by a current weighting factor, if this is smaller than the last for this frequency component calculated weighting factor, and wherein a frequency component is multiplied by the last for this frequency component calculated weighting factor, if this smaller is, than the current weighting factor.
- a low-rate speech codec is understood to mean a speech codec which delivers a data rate which is less than 5 kbit per second.
- the invention is based first of all on the knowledge that when using low voice codecs only a good voice quality can be achieved if the artefacts already explained above are avoided or reduced as far as possible. This could be recognized by the use of elaborate simulation tools specially created for this purpose.
- the invention is based on the finding that artifacts in the background signal, in particular during speech pauses, are reduced as a result of the special use of current or lastly calculated weighting factors, as likewise complex simulations have shown.
- FIG. 1 shows a block diagram of a method for speech processing. This method can be roughly divided into the cooperative blocks noise suppression and downstream low-pitch speech codec NSC.
- a low-pitch speech codec for example, which provides a data rate of 4 kbit per second, is known as such, which is not discussed in more detail here.
- the method of noise suppression can be divided into several function blocks, which are explained below.
- the blocks Analysis AN and Synthesis SY form the frame of the method for noise suppression.
- a segmentation (not shown in FIG. 1) before the analysis AN of the input signal and the block sizes used are matched to the lower-rate speech codec in such a way that the algorithmic delay of the signal caused by the noise suppression remains as low as possible.
- 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 forwarding of the processed data to the speech codec can also be carried out in segments with the given block length.
- the AN analysis can comprise windowing, zero-padding and a transformation into the frequency domain by means of a Fourier transformation, and the synthesis SY a backward transformation by an inverse Fourier transformation into the time domain and a signal reconstruction according to the overlap-add method.
- the frequency components resulting from the analysis AN have a real part and an imaginary part or a magnitude and phase.
- the magnitudes of various adjacent frequency components are initially combined to form a frequency group for reducing effort, for example, using a bar chart FGZU1.
- a gain calculation VB is performed 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 ratio can be derived from the power density spectrum of the perturbed input signal and the a-priori noise estimate GS.
- the a posteriori signal-to-noise ratio can be calculated from the power density spectrum of the perturbed input signal and the output of a buffer P, which in turn are supplied by a frequency group summary FGZU2 combined corrected frequency components.
- the a-priori noise estimation the gain calculation, the buffering of the signal amplitude modified for noise suppression and the minimum filter are performed only in a few subbands.
- the magnitude of the input signal transformed into the frequency domain and of the signal modified for interference signal suppression with two blocks for frequency group summation are combined into subbands.
- the width of the subbands is based on the Bark scale and therefore varies with the frequency.
- the output of each frequency group of the minimum filter is distributed by the frequency group decomposition block to the corresponding frequency components or Fourier coefficients.
- the magnitude of the input signal combined into frequency groups can also be multiplied element by element with the output signal of the minimum filter.
- the frequency-grouped signal of the noise reduction-modified magnitude values is stored in the buffering block.
- the output signals of the a-priori noise estimation and buffering serve, in addition to the magnitude values of the input signal combined in frequency groups, to calculate the gain calculation.
- the gain calculation results in weighting factors which are explained in more detail below - Minimum filters are supplied.
- the minimum filter determines the weighting factors provided for multiplication by the frequency components of the frequency groups.
- Disturbed speech signals picked up by a microphone are converted into an incoming digital speech signal s (k) affected by interference n (k) by means of a scanning device and a subsequent analog-to-digital conversion.
- This input signal is temporally segmented into blocks (block, m) (101), and the blocks (block, m) are mapped in time order by a transformation into the frequency domain to I frequency components f (i, m), where m the time and i represent the frequency. This can be done for example by a Fourier transformation. If the Fourier coefficients of the input signal are denoted by X (i, m), the values
- ⁇ 2 may be referred to as frequency components.
- the frequency components of a speech signal f (i, m) are multiplied by a weighting factor H (i, m) according to segmentation 101 explained above and transformation into the frequency range 102, wherein the weighting factor is calculated, 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 perturbed input signal and the a-priori noise estimate.
- the a posteriori signal-to-noise ratio may be from the power density spectrum of the defective input signal and the output of the buffering.
- the frequency or frequency component-dependent weighting factor is time-variable and is continuously determined according to the time-varying frequency components.
- the realization of a minimum filter for multiplication with a frequency component f (i, m) is not always based on the weighting factor H (i, m) actually calculated for this frequency component, but rather on the latter . So in the previous step, for this frequency component calculated weighting factor H (i, m-1) is smaller than the current weighting factor, the last, ie in the previous step, for this frequency component calculated weighting factor H (i, m-1) 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 last weighting factor 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 may also include a processor CPU and a memory device SPE.
- PE program-controlled processor device
- a microcontroller which may also include a processor CPU and a memory device SPE.
- the processor device PE further components belonging to the processor device, controlled by the processor device or controlling the processor device, whose function is sufficiently known to a person skilled in the art in connection with a processor device, and to which therefore will not be discussed here.
- the different components can exchange data with the processor device PE via a bus system BUS or input / output interfaces IOS and optionally suitable controllers (not shown).
- the processor device PE may be part of an electronic device, such as a communication terminal, or a mobile phone and also control other procedures and applications specific to the electronic device.
- the memory device SPE which may also be one or more volatile or nonvolatile RAM or ROM memory devices, or parts of the memory device SPE may be implemented as part of the processor device (shown in FIG.) Or as an external memory device (Not shown in Figure) be realized, which is located outside the processor device PE or even outside of the device containing the processor device PE and connected by lines or a bus system to the processor device PE.
- the program data which are used to control the device and the method for voice processing and noise suppression, stored. It is within the scope of expert action to implement above-mentioned functional components by program-controlled processors or microcircuits specially provided for this purpose.
- a digital signal processor DSP may be provided in order to carry out the steps of the methods explained above in whole or in part.
Description
Die Erfindung betrifft ein Verfahren gemäss Anspruch 1 und eine Anordnung gemäss Anspruch 3 zur Sprachverarbeitung, insbesondere eines gestörten Sprachsignals.The invention relates to a method according to
Die rasante technische Entwicklung im Bereich der Mobilkommunikation hat in den letzten Jahren zu ständig erhöhten Anforderungen an die Sprachverärbeitung, insbesondere die Sprachcodierung und die Störgeräuschunterdrückung geführt, was nicht zuletzt auf eine zunehmende Verknappung an Bandbreite und ständig wachsende Anforderungen an die Sprachqualität zurückzuführen ist.The rapid technical development in the field of mobile communications has led to ever-increasing demands on voice processing, in particular speech coding and noise suppression in recent years, not least due to an increasing shortage of bandwidth and ever-increasing voice quality requirements.
Ein wesentlicher Bestandteil der Sprachverarbeitung besteht darin, das Störsignal bzw. Störgeräusch, mit dem ein beispielsweise durch ein Mikrofon aufgenommenes Sprachsignal üblicherweise 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 the speech processing is to estimate the interference signal or noise with which a voice signal picked up, for example, by a microphone is usually afflicted, and optionally to suppress it in the input signal in order to transmit as possible only the voice signal. However, common methods for noise suppression often result in unwanted artifacts, also called musical tones, in the background signal.
Das Dokument WO-9 967 774 offenbart eine Lösung zur. Unterdrüchung von solchen Stärgeräuschen.Document WO-9 967 774 discloses a solution to. Suppression of such strong sounds.
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 voice processing, which allows a transmission of low-speed voice 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 developments emerge 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 Frequenzkomponente mit einem 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 Frequenzkomponente berechneten Gewichtungsfaktor multipliziert wird, wenn dieser kleiner ist, als der aktuelle Gewichtungsfaktor. Unter einem niederratigen Sprachcodec versteht man dabei insbesondere einen Sprachcodec, der eine Datenrate, die kleiner als 5 kBit pro Sekunde ist, liefert.The invention is therefore based initially on the idea of the frequency components of a speech signal having an interference signal before coding by a low-rate To multiply speech codec with time-varying frequency-dependent weighting factors, wherein a frequency component is multiplied by a current weighting factor, if this is smaller than the last for this frequency component calculated weighting factor, and wherein a frequency component is multiplied by the last for this frequency component calculated weighting factor, if this smaller is, than the current weighting factor. In particular, a low-rate speech codec is understood to mean a speech codec which delivers a data rate which is less than 5 kbit per second.
Dadurch wird erreicht, dass das einem Sprachsignal beaufschlagte Störsignal so gedämpft wird, dass bei geringem Rechen- oder Speicheraufwand Sprache mit guter Qualität übertragen werden kann.This ensures that the noise signal applied to a speech signal is so attenuated that speech can be transmitted with good quality at a low computational or memory expense.
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 based first of all on the knowledge that when using low voice codecs only a good voice quality can be achieved if the artefacts already explained above are avoided or reduced as far as possible. This could be recognized by the use of elaborate 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 finding that artifacts in the background signal, in particular during speech pauses, are reduced as a result of the special use of current or lastly calculated weighting factors, as likewise complex simulations have shown.
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 Sekunde liegt, liefert, wurde schließlich ebenfalls durch umfangreiche Simulationen bestätigt.This advantageous effect of the invention, ie the combination of a special method for noise suppression with a low-pitch speech codec, which in particular provides a data rate of between 3 kbit per second and 5 kbit per second, was finally confirmed by extensive simulations as well.
Die in weiteren oder abhängigen Ansprüchen beschriebenen Weiterbildungen, Ausgestaltungen und Ausführungsvarianten sind sowohl in Kombination mit den Verfahren als auch in Kombination mit den Anordnungen in der Erfindung enthalten.The further developments, embodiments and variants described in further or dependent claims are contained both in combination with the methods and in combination with the arrangements in the invention.
Die Erfindung wird im folgenden anhand bevorzugter Ausführungsbeispiele näher beschrieben, wobei die darin enthaltenen Merkmale auch in anderen Kombinationen durch die Erfindung umfasst sein können. Zur Erläuterung dieser Ausführungsbeispiele sollen nachstehend aufgelistete Figuren dienen:
Figur 1 vereinfachtes Blockschaltbild eines Verfahrens zur Sprachverarbeitung;Figur 2 Flussdiagramm eines Verfahrens zur Störgeräuschunterdrückung;- Figur 3 vereinfachtes Blockschaltbild einer Anordnung zur Sprachverarbeitung.
- Figure 1 simplified block diagram of a method for speech processing;
- Figure 2 flowchart of a method for noise reduction;
- Figure 3 simplified block diagram of an arrangement for speech processing.
Figur 1 zeigt ein Blockschaltbild eines Verfahrens zur Sprachverarbeitung. Dieses Verfahren lässt sich grob in die zusammenwirkenden Blöcke Störgeräuschunterdrückung 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 näher darauf eingegangen wird.FIG. 1 shows a block diagram of a method for speech processing. This method can be roughly divided into the cooperative blocks noise suppression and downstream low-pitch speech codec NSC. A low-pitch speech codec, for example, which provides a data rate of 4 kbit per second, is known as such, which is not discussed in more detail here.
Das Verfahren zur Störgeräuschunterdrückung kann in mehrere Funktionsblöcke unterteilt werden, die im folgenden erläutert werden.The method of noise suppression can be divided into several function blocks, which are explained below.
Die Blöcke Analyse AN und Synthese SY bilden den Rahmen des Verfahrens zur Geräuschunterdrückung. Eine vor einer Analyse AN stattfindende Segmentierung (in Figur nicht dargestellt) des Eingangssignals, sowie die verwendeten Blockgrößen sind auf den niederratigen Sprachcodec derart abgestimmt, dass die durch die Störgeräuschunterdrückung verursachte algorithmische Verzögerung des Signals möglichst gering bleibt. Die Segmentierung des Eingangssignals x(k) erfolgt beispielsweise in Blöcke zu 20ms bei einer Abtastrate von 8kHz. Die Weitergabe der prozessierten Daten an den Sprachcodec kann segmentweise ebenfalls mit der angegebenen Blocklänge erfolgen.The blocks Analysis AN and Synthesis SY form the frame of the method for noise suppression. A segmentation (not shown in FIG. 1) before the analysis AN of the input signal and the block sizes used are matched to the lower-rate speech codec in such a way that the algorithmic delay of the signal caused by the noise suppression remains as low as possible. 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 forwarding of the processed data to the speech codec can also be carried out in segments with the given block length.
Die Analyse AN kann dabei eine Fensterung, Zero-Padding und eine Transformation in den Frequenzbereich durch eine Fouriertransformation umfassen, und die Synthese SY eine Rücktransformation durch eine inverse Fouriertransformationin den Zeitbereich und eine Signalrekonstruktion nach dem Overlap Add Verfahren.The AN analysis can comprise windowing, zero-padding and a transformation into the frequency domain by means of a Fourier transformation, and the synthesis SY a backward transformation by an inverse Fourier transformation into the time domain and a signal reconstruction according to the overlap-add method.
Die aus der Analyse AN hervorgehenden Frequenzkomponenten weisen einen Real- und einen Imaginärteil auf bzw. eine Magnitude und Phase. Die Magnituden verschiedener nebeneinanderliegender Frequenzkomponenten werden zur Aufwandsreduzierung beispielsweise anhand einer Barktabelle zunächst zu Frequenzgruppen zusammengefasst FGZU1.The frequency components resulting from the analysis AN have a real part and an imaginary part or a magnitude and phase. The magnitudes of various adjacent frequency components are initially combined to form a frequency group for reducing effort, for example, using a bar chart FGZU1.
Für jede Frequenzgruppe wird anhand eines A-priori und eines A-posteriori Signal-zu-Rauschverhältnisses eine Verstärkungsberechnung VB durchgeführt, welche Gewichtungsfaktoren für die Magnituden der einzelnen Frequenzgruppen zum Ergebnis hat. Das A-priori Signal-zu-Rauschverhältnis kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und der A-priori Geräuschschätzung GS abgeleitet werden. Das A-posteriori Signal-zu-Rauschverhältnis kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und dem Ausgangssignal einer Pufferung P, der wiederum durch eine Frequenzgruppenzusammenfassung FGZU2 zusammengefasste korrigierte Frequenzkomponenten zugeführt werden, berechnet werden.For each frequency group, a gain calculation VB is performed 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 ratio can be derived from the power density spectrum of the perturbed input signal and the a-priori noise estimate GS. The a posteriori signal-to-noise ratio can be calculated from the power density spectrum of the perturbed input signal and the output of a buffer P, which in turn are supplied by a frequency group summary FGZU2 combined corrected frequency components.
Vor einer Zerlegung FGZE der zuvor zu Frequenzgruppen zusammengefassten Frequenzkomponenten und einer Multiplikation der Frequenzkomponenten mit jeweils dem für eine entsprechende Frequenzgruppe berechneten Gewichtungsfaktor zur Störgeräuschunterdrückung, werden die Gewichtungsfaktoren einer sogenannten Minimum-Filterung MF unterzogen, welche später anhand Figur 2 näher erläutert wird.Before decomposing FGZE of the frequency components previously combined into frequency groups and multiplying the frequency components by a corresponding one for each Frequency group calculated weighting factor for noise reduction, the weighting factors of a so-called minimum filtering MF subjected, which will be explained later with reference to FIG 2.
Zur Störgeräuschschätzung erfolgt also im wesentlichen eine Schätzung der Leistungsdichte des Hintergrundgeräusches aus dem Eingangssignal. Zur Reduktion der benötigten Rechenleistung sowie des Speicherverbrauchs werden die A-priori Geräuschschätzung, die Verstärkungsberechnung, die Pufferung der zur Störsignalunterdrückung modifizierten Signalmagnitude und das Minimum-Filter nur in wenigen Teilbändern durchgeführt. Hierzu werden die Magnitude des in den Frequenzbereich transformierten Eingangssignals und des zur Störsignalunterdrückung modifizierten Signals mit zwei Blöcken zur Frequenzgruppen-Zusammenfassung in Teilbänder zusammengefasst. Die Breite der Teilbänder orientiert sich dabei an der Bark-Skala und variiert daher mit der Frequenz. Das Ausgangssignal jeder Frequenzgruppe des Minimum-Filters wird durch den Block Frequenzgruppen-Zerlegung auf die entsprechenden Frequenzkomponenten bzw. Fourier-Koeffizienten verteilt. Zur Berechnung des Eingangssignals des Pufferungs-Blocks kann in einer anderen Ausführungsvariante anstelle einer Frequenzgruppen-Zusammenfassung des zur Störsignalunterdrückung modifizierten Signals, auch die in Frequenzgruppen zusammengefasste Magnitude des Eingangssignals elementweise mit dem Ausgangssignal des Minimum-Filters multipliziert werden.For noise estimation, therefore, an estimate of the power density of the background noise from the input signal is essentially made. To reduce the required computing power and the memory consumption, the a-priori noise estimation, the gain calculation, the buffering of the signal amplitude modified for noise suppression and the minimum filter are performed only in a few subbands. For this purpose, the magnitude of the input signal transformed into the frequency domain and of the signal modified for interference signal suppression with two blocks for frequency group summation are combined into subbands. The width of the subbands is based on the Bark scale and therefore varies with the frequency. The output of each frequency group of the minimum filter is distributed by the frequency group decomposition block to the corresponding frequency components or Fourier coefficients. 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 into frequency groups can also be multiplied element by element with the output signal of the minimum filter.
Neben der Störgeräuschschätzung erfolgt eine A-posteriori Schätzung des Sprachsignalanteils. Hierzu wird das in Frequenzgruppen zusammengefasste Signal der zur Geräuschreduktion modifizierten Magnitudenwerte im Block Pufferung gespeichert. Die Ausgangssignale der A-priori Geräuschschätzung und der Pufferung dienen neben der Magnitudenwerte des in Frequenzgruppen zusammengefassten Eingangssignals zur Berechnung der Verstärkungsberechnung. Aus der Verstärkungsberechnung resultieren Gewichtungsfaktoren, die einem - unten näher erläuterten - Minimum-Filter zugeführt werden. Das Minimum-Filter ermittelt schließlich die für die Multiplikation mit den Frequenzkomponenten der Frequenzgruppen vorgesehenen Gewichtungsfaktoren.In addition to noise estimation, there is an a posteriori estimation of the speech signal component. For this purpose, the frequency-grouped signal of the noise reduction-modified magnitude values is stored in the buffering block. The output signals of the a-priori noise estimation and buffering serve, in addition to the magnitude values of the input signal combined in frequency groups, to calculate the gain calculation. The gain calculation results in weighting factors which are explained in more detail below - Minimum filters are supplied. Finally, the minimum filter determines the weighting factors provided for multiplication by the frequency components of the frequency groups.
Anhand eines in Figur 2 dargestellten Flussdiagramms wird nun eine vereinfachte Ausführungsvariante zur Störgeräuschunterdrückung eines Sprachsignals näher erläutert. Dabei kommen die in Figur 1 dargestellten Blöcke Frequenzgruppenzusammenfassung FGZU1, FGZU2 und Frequenzgruppenzerlegung nicht zum Einsatz.Based on a flowchart shown in Figure 2, a simplified embodiment for noise suppression of a speech signal will now be explained in more detail. 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 Frequenzkomponenten 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)|^2 als Frequenzkomponenten bezeichnet werden.Disturbed speech signals picked up by a microphone are converted into an incoming digital speech signal s (k) affected by interference n (k) by means of a scanning device and a subsequent analog-to-digital conversion. This input signal is temporally segmented into blocks (block, m) (101), and the blocks (block, m) are mapped in time order by a transformation into the frequency domain to I frequency components f (i, m), where m the time and i represent the frequency. This can be done for example by a Fourier transformation. If the Fourier coefficients of the input signal are denoted by X (i, m), the values | X (i, m) | ^ 2 may be referred to as 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-Rauschverhältnis kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und der A-priori Geräuschschätzung abgeleitet werden. Das A-posteriori Signal-zu Rauschverhältnis kann aus dem Leistungsdichtespektrum des gestörten Eingangssignals und dem Ausgangssignal der Pufferung berechnet werden.The frequency components of a speech signal f (i, m) are multiplied by a weighting factor H (i, m) according to
Der frequenz- oder frequenzkomponentenabhängige Gewichtungsfaktor ist dabei zeitlich veränderlich und wird entsprechend der zeitlich veränderlichen Frequenzkomponenten fortlaufend aktuell ermittelt. Um unerwünschte Artefakte im Hintergrundsignal zu vermeiden, wird allerdings zur Realisierung eines Minimum-Filters zur Multiplikation mit einer Frequenzkomponente f(i,m) nicht immer der aktuell für diese Frequenzkomponente berechnete Gewichtungsfaktor H(i,m) herangezogen, sondern dann, wenn der zuletzt, also im vorhergehende Schritt, für diese Frequenzkomponente berechnete Gewichtungsfaktor H(i,m-1) kleiner ist, als der aktuelle Gewichtungsfaktor, der zuletzt, also im vorhergehende Schritt, für diese Frequenzkomponente berechnete Gewichtungsfaktor H (i,m-1) herangezogen wird.The frequency or frequency component-dependent weighting factor is time-variable and is continuously determined according to the time-varying frequency components. In order to avoid unwanted artifacts in the background signal, however, the realization of a minimum filter for multiplication with a frequency component f (i, m) is not always based on the weighting factor H (i, m) actually calculated for this frequency component, but rather on the latter , So in the previous step, for this frequency component calculated weighting factor H (i, m-1) is smaller than the current weighting factor, the last, ie in the previous step, for this frequency component calculated weighting factor H (i, m-1) is used ,
Eine Ausführungsvariante der Erfindung sieht vor, dass 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.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 last weighting factor 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 Frequenzkomponente auswählt. Wird der feste Schwellwert 0.76 durch den aktuellen Gewichtungsfaktor überschritten, so findet keine Modifikation der Frequenzkomponente statt.This can be realized by a filter which compares the current weight factor with the time weight factor at the same frequency and selects the smaller of the two values for the application to the frequency component. If the fixed threshold 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.FIG. 4 shows a program-controlled processor device PE, such as a microcontroller, which may also include a processor CPU and a memory device SPE.
Je nach Ausführungsvariante können dabei innerhalb oder außerhalb der Prozessoreinrichtung PE weitere - der Prozessoreinrichtung zugeordnete, zur Prozessoreinrichtung gehörende, durch die Prozessoreinrichtung gesteuerte oder die Prozessoreinrichtung steuernde - Komponenten angeordnet sein, deren 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/Ausgabeschnittstellen 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.Depending on the embodiment, within or outside the processor device PE further components belonging to the processor device, controlled by the processor device or controlling the processor device, whose function is sufficiently known to a person skilled in the art in connection with a processor device, and to which therefore will not be discussed here. The different components can exchange data with the processor device PE via a bus system BUS or input / output interfaces IOS and optionally suitable controllers (not shown). In this case, the processor device PE may be part of an electronic device, such as a communication terminal, or a mobile phone and also control other procedures 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, the memory device SPE, which may also be one or more volatile or nonvolatile RAM or ROM memory devices, or parts of the memory device SPE may be implemented as part of the processor device (shown in FIG.) Or as an external memory device (Not shown in Figure) be realized, which is located outside the processor device PE or even outside of the device containing the processor device PE and connected by lines or a bus system to the processor device PE.
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 Mikroschaltungen zu realisieren.In the storage device SPE, the program data, which are used to control the device and the method for voice processing and noise suppression, stored. It is within the scope of expert action to implement above-mentioned functional components by program-controlled processors or microcircuits specially provided for this purpose.
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. About the input / output interface IOS the faulty digital voice signals of the processor device PE can be supplied. In addition to the processor CPU, a digital signal processor DSP may be provided in order to carry out the steps of the methods explained above in whole or in part.
Claims (4)
- Method for voice processing,- in which an incoming digital voice signal s(k) is segmented (101) chronologically into blocks (block,m),- in which the blocks (block,m) are mapped (102) in chronological order by a transformation in the frequency range to frequency components (f,i) in each case,- the frequency components are multiplied by chronologically modifiable frequency-dependent weighting factors,- 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,- where a frequency component is multiplied by the weighting factor last calculated for this frequency component if this is smaller than the current weighting factor, and- for which the frequency components weighted in this way are fed back after a back transformation in the time range to a low-rate voice codec.
- Method in accordance with claim 1, in which
a frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor lies above a threshold value, that is when the weighting factor last calculated for this frequency component is smaller than the current weighting factor. - System for noise suppression- with an input (IOS) for digital voice signals and- with a processor unit (PE), which is designed in such a way that- an incoming digital voice signal s(k) is chronologically segmented (101) into blocks (block,m),- the blocks (block,m) are mapped (102) in chronological order by a transformation in the frequency range onto frequency components (f,i) in each case,- the frequency components are multiplied by chronologically modifiable frequency-dependent weighting factors,- where a frequency component is multiplied by the current weighting factor if this is smaller than the last weighting factor calculated for this frequency component, and- where a frequency component is multiplied by the weighting factor last calculated for this frequency component if this is smaller than the current weighting factor, and- for which the frequency components weighted in this way are fed back after a back transformation in the time range to a low-rate voice codec.
- System according to claim 3, in which- a frequency component is multiplied by the current weighting factor if the frequency-dependent weighting factor lies above a threshold value, that is when the weighting factor last calculated for this frequency component is smaller than the current weighting factor.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE10150519.1A DE10150519B4 (en) | 2001-10-12 | 2001-10-12 | Method and arrangement for speech processing |
| DE10150519 | 2001-10-12 | ||
| PCT/DE2002/003740 WO2003034407A1 (en) | 2001-10-12 | 2002-10-02 | Method and system for reducing a voice signal noise |
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| Publication Number | Publication Date |
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| EP1435089A1 EP1435089A1 (en) | 2004-07-07 |
| EP1435089B1 true EP1435089B1 (en) | 2006-04-12 |
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|---|---|---|---|
| EP02776772A Expired - Lifetime EP1435089B1 (en) | 2001-10-12 | 2002-10-02 | Method and system for reducing a voice signal noise |
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| EP (1) | EP1435089B1 (en) |
| CN (1) | CN1241172C (en) |
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| DE10150519B4 (en) * | 2001-10-12 | 2014-01-09 | Hewlett-Packard Development Co., L.P. | Method and arrangement for speech processing |
| US7945058B2 (en) * | 2006-07-27 | 2011-05-17 | Himax Technologies Limited | Noise reduction system |
| ATE528749T1 (en) * | 2007-05-21 | 2011-10-15 | Harman Becker Automotive Sys | METHOD FOR PROCESSING AN ACOUSTIC INPUT SIGNAL FOR THE PURPOSE OF TRANSMITTING AN OUTPUT SIGNAL WITH REDUCED VOLUME |
| JP6135106B2 (en) * | 2012-11-29 | 2017-05-31 | 富士通株式会社 | Speech enhancement device, speech enhancement method, and computer program for speech enhancement |
| CN106201015B (en) * | 2016-07-08 | 2019-04-19 | 百度在线网络技术（北京）有限公司 | Pronunciation inputting method and device based on input method application software |
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- 2002-10-02 US US10/492,434 patent/US7392177B2/en not_active Expired - Fee Related
- 2002-10-02 WO PCT/DE2002/003740 patent/WO2003034407A1/en not_active Application Discontinuation
- 2002-10-02 EP EP02776772A patent/EP1435089B1/en not_active Expired - Lifetime
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2008
- 2008-05-20 US US12/123,966 patent/US8005669B2/en not_active Expired - Fee Related
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| EP1435089A1 (en) | 2004-07-07 |
| US20040186711A1 (en) | 2004-09-23 |
| DE10150519B4 (en) | 2014-01-09 |
| CN1568503A (en) | 2005-01-19 |
| CN1241172C (en) | 2006-02-08 |
| US7392177B2 (en) | 2008-06-24 |
| US20090132241A1 (en) | 2009-05-21 |
| WO2003034407A1 (en) | 2003-04-24 |
| DE10150519A1 (en) | 2003-04-17 |
| US8005669B2 (en) | 2011-08-23 |
| DE50206411D1 (en) | 2006-05-24 |
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