Method for adaptively encoding an audio signal in dependence on noise information for higher encoding accuracy

Abstract

An audio encoder for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to obtain a noise information describing a noise included in the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise included in the audio signal than for parts of the audio signal that are more affected by the noise included in the audio signal.

Claims

1. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to select the codebook entry using a perceptual weighting filter; wherein the audio encoder is configured to adjust the perceptual weighing filter such that parts of the speech signal that are less affected by the noise are weighted more for the selection of the codebook entry than parts of the speech signal that are more affected by the noise.

2. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to adaptively encode the audio signal by adjusting a perceptual objective function used for encoding the audio signal in dependence on the noise information.

3. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to simultaneously encode the audio signal and reduce the noise in the encoded representation of the audio signal, by adaptively encoding the audio signal in dependence on the noise information.

4. The audio encoder apparatus according to claim 1, wherein the noise information is a signal-to-noise ratio.

5. The audio encoder apparatus according to claim 1, wherein the noise information is an estimated shape of the noise comprised by the audio signal.

6. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to estimate a contribution of a vocal tract on the speech signal, and to remove the estimated contribution of the vocal tract from the speech signal in order to acquire the residual signal.

7. The audio encoder apparatus according to claim 6, wherein the audio encoder is configured to estimate the contribution of the vocal tract on the speech signal using linear prediction.

8. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to adjust the perceptual weighting filter such that an effect of the noise on the selection of the codebook entry is reduced.

9. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to adjust the perceptual weighting filter such that an error between the parts of the residual signal that are less affected by the noise and the corresponding parts of a quantized residual signal is reduced.

10. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to select the codebook entry for the residual signal such that a synthesized weighted quantization error of the residual signal weighted with the perceptual weighting filter is reduced.

11. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to select the codebook entry using the distance function:
WH(x{circumflex over (x)}).sup.2 wherein x represents the residual signal, wherein {circumflex over (x)} represents the quantized residual signal, wherein W represents the perceptual weighting filter, and wherein H represents a quantized vocal tract synthesis filter.

12. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to use an estimate of a shape of the noise which is available in the audio encoder for voice activity detection as the noise information.

13. The audio encoder apparatus according to claim 1, wherein the audio encoder is configured to derive linear prediction coefficients from the noise information, to thereby determine a linear prediction fit (A.sub.BCK), and to use the linear prediction fit (A.sub.BCK) in the perceptual weighting filter.

14. The audio encoder apparatus according to claim 13, wherein the audio encoder is configured to adjust the perceptual weighting filter using the formula:
W(z)=A(z/.sub.1)A.sub.BCK(z/.sub.2)H.sub.de-emph(z) wherein W represents the perceptual weighting filter, wherein A represents a vocal tract model, A.sub.BCK represents the linear prediction fit, H.sub.de-emph represents a quantized vocal tract synthesis filter, .sub.1=0.92, and .sub.2 is a parameter with which an amount of noise suppression is adjustable.

15. A method for providing an encoded representation on the basis of an audio signal, wherein the method comprises: acquiring a noise information describing a noise comprised by the audio signal; and adaptively encoding the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than parts of the audio signal that are more affected by the noise comprised by the audio signal, wherein frequency components that are less corrupted by the noise are quantized with less error whereas components which are likely to comprise errors from the noise comprising a lower weight in the quantization process; wherein the audio signal is a speech signal, deriving a residual signal from the speech signal, encoding the residual signal using a codebook; selecting a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; selecting the codebook entry using a perceptual weighting filter; adjusting the perceptual weighing filter such that parts of the speech signal that are less affected by the noise are weighted more for the selection of the codebook entry than parts of the speech signal that are more affected by the noise.

16. A non-transitory digital storage medium having a computer program stored thereon to perform the method for providing an encoded representation on the basis of an audio signal, wherein the method comprises: acquiring a noise information describing a noise comprised by the audio signal; and adaptively encoding the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than parts of the audio signal that are more affected by the noise comprised by the audio signal, wherein frequency components that are less corrupted by the noise are quantized with less error whereas components which are likely to comprise errors from the noise comprising a lower weight in the quantization process, wherein the audio signal is a speech signal, deriving a residual signal from the speech signal, encoding the residual signal using a codebook; selecting a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; selecting the codebook entry using a perceptual weighting filter; adjusting the perceptual weighing filter such that parts of the speech signal that are less affected by the noise are weighted more for the selection of the codebook entry than parts of the speech signal that are more affected by the noise; when said computer program is run by a computer.

17. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to select the codebook entry using a perceptual weighting filter; wherein the audio encoder is configured to adjust the perceptual weighting filter such that an effect of the noise on the selection of the codebook entry is reduced.

18. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to select the codebook entry using a perceptual weighting filter; wherein the audio encoder is configured to adjust the perceptual weighting filter such that an error between the parts of the residual signal that are less affected by the noise and the corresponding parts of a quantized residual signal is reduced.

19. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to select the codebook entry using a perceptual weighting filter; wherein the audio encoder is configured to select the codebook entry for the residual signal such that a synthesized weighted quantization error of the residual signal weighted with the perceptual weighting filter is reduced.

20. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to use an estimate of a shape of the noise which is available in the audio encoder for voice activity detection as the noise information.

21. An audio encoder apparatus for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to acquire a noise information describing a noise comprised by the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise comprised by the audio signal than for parts of the audio signal that are more affected by the noise comprised by the audio signal; wherein the audio signal is a speech signal, and wherein the audio encoder is configured to derive a residual signal from the speech signal and to encode the residual signal using a codebook; wherein the audio encoder is configured to select a codebook entry of a plurality of codebook entries of a codebook for encoding the residual signal in dependence on the noise information; wherein the audio encoder is configured to derive linear prediction coefficients from the noise information, to thereby determine a linear prediction fit (A.sub.BCK), and to use the linear prediction fit (A.sub.BCK) in the perceptual weighting filter.

22. The audio encoder apparatus according to claim 21, wherein the audio encoder is configured to adjust the perceptual weighting filter using the formula:
W(z)=A(z/.sub.1)A.sub.BCK(z/.sub.2)H.sub.de-emph(z) wherein W represents the perceptual weighting filter, wherein A represents a vocal tract model, A.sub.BCK represents the linear prediction fit, H.sub.de-emph represents a quantized vocal tract synthesis filter, .sub.1=0.92, and .sub.2 is a parameter with which an amount of noise suppression is adjustable.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) Embodiments of the present invention will be detailed subsequently referring to the appended drawings, in which:

(2) FIG. 1 shows a schematic block diagram of an audio encoder for providing an encoded representation on the basis of an audio signal, according to an embodiment;

(3) FIG. 2a shows a schematic block diagram of an audio encoder for providing an encoded representation on the basis of a speech signal, according to an embodiment;

(4) FIG. 2b shows a schematic block diagram of a codebook entry determiner, according to an embodiment;

(5) FIG. 3 shows in a diagram a magnitude of an estimate of the noise and a reconstructed spectrum for the noise plotted over frequency;

(6) FIG. 4 shows in a diagram a magnitude of linear prediction fits for the noise for different prediction orders plotted over frequency;

(7) FIG. 5 shows in a diagram a magnitude of an inverse of an original weighting filter and magnitudes of inverses of proposed weighting filters having different prediction orders plotted over frequency; and

(8) FIG. 6 shows a flow chart of a method for providing an encoded representation on the basis of an audio signal, according to an embodiment.

DETAILED DESCRIPTION OF THE INVENTION

(9) Equal or equivalent elements or elements with equal or equivalent functionality are denoted in the following description by equal or equivalent reference numerals.

(10) In the following description, a plurality of details are set forth to provide a more thorough explanation of embodiments of the present invention. However, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form rather than in detail in order to avoid obscuring embodiments of the present invention. In addition, features of the different embodiments described hereinafter may be combined with each other unless specifically noted otherwise.

(11) FIG. 1 shows a schematic block diagram of an audio encoder 100 for providing an encoded representation (or encoded audio signal) 102 on the basis of an audio signal 104. The audio encoder 100 is configured to obtain a noise information 106 describing a noise included in the audio signal 104 and to adaptively encode the audio signal 104 in dependence on the noise information 106 such that encoding accuracy is higher for parts of the audio signal 104 that are less affected by the noise included in the audio signal 104 than for parts of the audio signal that are more affected by the noise included in the audio signal 104.

(12) For example, the audio encoder 100 can comprise a noise estimator (or noise determiner or noise analyzer) 110 and a coder 112. The noise estimator 110 can be configured to obtain the noise information 106 describing the noise included in the audio signal 104. The coder 112 can be configured to adaptively encode the audio signal 104 in dependence on the noise information 106 such that encoding accuracy is higher for parts of the audio signal 104 that are less affected by the noise included in the audio signal 104 than for parts of the audio signal 104 that are more affected by the noise included in the audio signal 104.

(13) The noise estimator 110 and the coder 112 can be implemented by (or using) a hardware apparatus such as, for example, an integrated circuit, a field programmable gate array, a microprocessor, a programmable computer or an electronic circuit.

(14) In embodiments, the audio encoder 100 can be configured to simultaneously encode the audio signal 104 and reduce the noise in the encoded representation 102 of the audio signal 104 (or encoded audio signal) by adaptively encoding the audio signal 104 in dependence on the noise information 106.

(15) In embodiments, the audio encoder 100 can be configured to encode the audio signal 104 using a perceptual objective function. The perceptual objective function can be adjusted (or modified) in dependence on the noise information 106, thereby adaptively encoding the audio signal 104 in dependence on the noise information 106. The noise information 106 can be, for example, a signal-to-noise ratio or an estimated shape of the noise included in the audio signal 104.

(16) Embodiments of the present invention attempt to decrease listening effort or respectively increase intelligibility. Here it is important to note that embodiments may not in general provide the most accurate possible representation of the input signal but try to transmit such parts of the signal that listening effort or intelligibility is optimized. Specifically, embodiments may change the timbre of the signal, but in such a way that the transmitted signal reduces listening effort or is better for intelligibility than the accurately transmitted signal.

(17) According to some embodiments, the perceptual objective function of the codec is modified. In other words, embodiments do not explicitly suppress noise, but change the objective such that accuracy is higher in parts of the signal where signal to noise ratio is best. Equivalently, embodiments decrease signal distortion at those parts where SNR is high. Human listeners can then more easily understand the signal. Those parts of the signal which have low SNR are thereby transmitted with less accuracy but, since they contain mostly noise anyway, it is not important to encode such parts accurately. In other words, by focusing accuracy on high SNR parts, embodiments implicitly improve the SNR of the speech parts while decreasing the SNR of noise parts.

(18) Embodiments can be implemented or applied in any speech and audio codec, for example, in such codecs which employ a perceptual model. In effect, according to some embodiments the perceptual weighting function can be modified (or adjusted) based on the noise characteristic. For example, the average spectral envelope of the noise signal can be estimated and used to modify the perceptual objective function.

(19) Embodiments disclosed herein are applicable to speech codecs of the CELP-type (CELP=code-excited linear prediction) or other codecs in which the perceptual model can be expressed by a weighting filter. Embodiments however also can be used in TCX-type codecs (TCX=transform coded excitation) as well as other frequency-domain codecs. Further, a use case of embodiments may be speech coding but embodiments also can be employed more generally in any speech and audio codec. Since ACELP (ACELP =algebraic code excited linear prediction) is a typical application, application of embodiments in ACELP will be described in detail below. Application of embodiments in other codecs, including frequency domain codecs will then be obvious for those skilled in the art.

(20) A conventional approach for noise suppression in speech and audio codecs is to apply it as a separate pre-processing block with the purpose of removing noise before coding. However, by separating it to separate blocks there are two main disadvantages. First, since the noise-suppressor will generally not only remove noise but also distort the desired signal, the codec will thus attempt to encode a distorted signal accurately. The codec will therefore have a wrong target and efficiency and accuracy is lost. This can also be seen as a case of tandeming problem where subsequent blocks produce independent errors which add up. But joint noise suppression and coding embodiments avoid tandeming problems. Second, since the noise-suppressor is conventionally implemented in a separate pre-processing block, computational complexity and delay is high. In contrast to that, since according to embodiments the noise-suppressor is embedded in the codec it can be applied with very low computational complexity and delay. This will be especially beneficial in low-cost devices which do not have the computational capacity for conventional noise suppression.

(21) The description will further discuss application in the context of the AMR-WB codec (AMR-WB=adaptive multi-rate wideband), because that is at the date of writing the most commonly used speech codec. Embodiments can readily be applied on top of other speech codecs as well, such as 3GPP Enhanced Voice Services or G.718. Note that a usage of embodiments may be an add-on to existing standards since embodiments can be applied to codecs without changing the bitstream format.

(22) FIG. 2a shows a schematic block diagram of an audio encoder 100 for providing an encoded representation 102 on the basis of the speech signal 104, according to an embodiment. The audio encoder 100 can be configured to derive a residual signal 120 from the speech signal 104 and to encode the residual signal 120 using a codebook 122. In detail, the audio encoder 100 can be configured to select a codebook entry of a plurality of codebook entries of the codebook 122 for encoding the residual signal 120 in dependence on the noise information 106. For example, the audio encoder 100 can comprise a codebook entry determiner 124 comprising the codebook 122, wherein the codebook entry determiner 124 can be configured to select a codebook entry of a plurality of codebook entries of the codebook 122 for encoding the residual signal 120 in dependence on the noise information 106, thereby obtaining a quantized residual 126.

(23) The audio encoder 100 can be configured to estimate a contribution of a vocal tract on the speech signal 104 and to remove the estimated contribution of the vocal tract from the speech signal 104 in order to obtain the residual signal 120. For example, the audio encoder 100 can comprise a vocal tract estimator 130 and a vocal tract remover 132. The vocal tract estimator 130 can be configured to receive the speech signal 104, to estimate a contribution of the vocal tract on the speech signal 104 and to provide the estimated contribution of the vocal tract 128 on the speech signal 104 to the vocal tract remover 132. The vocal tract remover 132 can be configured to remove the estimated contribution of the vocal tract 128 from the speech signal 104 in order to obtain the residual signal 120. The contribution of the vocal tract on the speech signal 104 can be estimated, for example, using linear prediction.

(24) The audio encoder 100 can be configured to provide the quantized residual 126 and the estimated contribution of the vocal tract 128 (or filter parameters describing the estimated contribution 128 of the vocal tract 104) as encoded representation on the basis of the speech signal (or encoded speech signal).

(25) FIG. 2b shows a schematic block diagram of the codebook entry determiner 124 according to an embodiment. The codebook entry determiner 124 can comprise an optimizer 140 configured to select the codebook entry using a perceptual weighting filter W. For example, the optimizer 140 can be configured to select the codebook entry for the residual signal 120 such that a synthesized weighted quantization error of the residual signal 126 weighted with the perceptual weighting filter W is reduced (or minimized). For example, the optimizer 130 can be configured to select the codebook entry using the distance function:
WH(x{circumflex over (x)}).sup.2
wherein x represents the residual signal, wherein {circumflex over (x)} represents the quantized residual signal, wherein W represents the perceptual weighting filter, and wherein H represents a quantized vocal tract synthesis filter. Thereby, W and H can be convolution matrices.

(26) The codebook entry determiner 124 can comprise a quantized vocal tract synthesis filter determiner 144 configured to determine a quantized vocal tract synthesis filter H from the estimated contribution of the vocal tract A(z).

(27) Further, the codebook entry determiner 124 can comprise a perceptual weighting filter adjuster 142 configured to adjust the perceptual weighting filter W such that an effect of the noise on the selection of the codebook entry is reduced. For example, the perceptual weighting filter W can be adjusted such that parts of the speech signal that are less affected by the noise are weighted more for the selection of the codebook entry than parts of the speech signal that are more affected by the noise. Further (or alternatively), the perceptual weighting filter W can be adjusted such that an error between the parts of the residual signal 120 that are less affected by the noise and the corresponding parts of the quantized residual 126 signal is reduced.

(28) The perceptual weighting filter adjuster 142 can be configured to derive linear prediction coefficients from the noise information (106), to thereby determine a linear prediction fit (A_BCK), and to use the linear prediction fit (A_BCK) in the perceptual weighting filter (W). For example, perceptual weighting filter adjuster 142 can be configured to adjust the perceptual weighting filter W using the formula:
W(z)=A(z/.sub.1)A.sub.BCK(z/.sub.2)H.sub.de-emph(z)
wherein W represents the perceptual weighting filter, wherein A represents a vocal tract model, A.sub.BCK represents the linear prediction fit, H.sub.de-emph represents a de-emphasis filter, .sub.1=0.92, and .sub.2 is a parameter with which an amount of noise suppression is adjustable. Thereby, H.sub.de-emph can be equal to 1/(10.68z.sup.1).

(29) In other words, the AMR-WB codec uses algebraic code-excited linear prediction (ACELP) for parametrizing the speech signal 104. This means that first the contribution of the vocal tract, A(z), is estimated with linear prediction and removed and then the residual signal is parametrized using an algebraic codebook. For finding the best codebook entry, a perceptual distance between the original residual and the codebook entries can be minimized. The distance function can be written as WH(x{circumflex over (x)}).sup.2, where x and {circumflex over (x)} are the original and quantized residuals, W and H are the convolution matrices corresponding, respectively, to H(z)=1/(z), the quantized vocal tract synthesis filter and W(z), the perceptual weighting, which is typically chosen as W(z)=A(z/.sub.1)H.sub.de-emph(z) with .sub.1=0.92. The residual x has been computed with the quantized vocal tract analysis filter.

(30) In an application scenario, additive far-end noise may be present in the incoming speech signal. Thus, the signal is y(t)=s(t)+n(t). In this case, both the vocal tract model, A(z), and the original residual contain noise. Starting from the simplification of ignoring the noise in the vocal tract model and focusing on the noise in the residual, the idea (according to an embodiment) is to guide the perceptual weighting such that the effects of the additive noise are reduced in the selection of the residual. Whereas normally the error between the original and quantized residual is wanted to resemble the speech spectral envelope, according to embodiments the error in the region which is considered more robust to noise is reduced. In other words, according to embodiments, the frequency components that are less corrupted by the noise are quantized with less error whereas components with low magnitudes which are likely to contain errors from the noise have a lower weight in the quantization process.

(31) To take into account the effect of noise on the desired signal, first an estimate of the noise signal is needed. Noise estimation is classic topic for which many methods exist. Some embodiments provide a low-complexity method according to which information that already exists in the encoder is used. In an approach, the estimate of the shape of the background noise which is stored for the voice activity detection (VAD) can be used. This estimate contains the level of the background noise in 12 frequency bands with increasing width. A spectrum can be constructed from this estimate by mapping it to a linear frequency scale with interpolation between the original data points. An example of the original background estimate and the reconstructed spectrum is shown in FIG. 3. In detail, FIG. 3 shows the original background estimate and the reconstructed spectrum for car noise with average SNR 10 dB. From the reconstructed spectrum the autocorrelation is computed and used to derive the pth order linear prediction (LP) coefficients with the Levinson-Durbin recursion. Examples of the obtained LP fits with p=2 . . . 6 are shown in FIG. 4. In detail, FIG. 4 shows the obtained linear prediction fits for the background noise with different prediction orders (p=2 . . . 6). The background noise is car noise with average SNR 10 dB.

(32) The obtained LP fit, A.sub.BCK(z) can be used as part of the weighting filter such that the new weighting filter can be calculated to
W(z)=A(z/.sub.1)A.sub.BCK(z/.sub.2)H.sub.de-emph(z).
Here .sub.2 is a parameter with which the amount of noise suppression can be adjusted. With .sub.2.fwdarw.0 the effect is small, while for .sub.21 a high noise suppression can be obtained.

(33) In FIG. 5, an example of the inverse of the original weighting filter as well as the inverse of the proposed weighting filter with different prediction orders is shown. For the figure, the de-emphasis filter has not been used. In other words, FIG. 5 shows the frequency responses of the inverse of the original and the proposed weighting filters with different prediction orders. The background noise is car noise with average SNR 10 dB.

(34) FIG. 6 shows a flow chart of a method for providing an encoded representation on the basis of an audio signal. The method comprises a step 202 of obtaining a noise information describing a noise included in the audio signal. Further, the method 200 comprises a step 204 of adaptively encoding the audio signal in dependence on the noise information such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise included in the audio signal than parts of the audio signal that are more affected by the noise included in the audio signal.

(35) Although some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block or item or feature of a corresponding apparatus. Some or all of the method steps may be executed by (or using) a hardware apparatus, like for example, a microprocessor, a programmable computer or an electronic circuit. In some embodiments, one or more of the most important method steps may be executed by such an apparatus.

(36) The inventive encoded audio signal can be stored on a digital storage medium or can be transmitted on a transmission medium such as a wireless transmission medium or a wired transmission medium such as the Internet.

(37) Depending on certain implementation requirements, embodiments of the invention can be implemented in hardware or in software. The implementation can be performed using a digital storage medium, for example a floppy disk, a DVD, a Blu-Ray, a CD, a ROM, a PROM, an EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Therefore, the digital storage medium may be computer readable.

(38) Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.

(39) Generally, embodiments of the present invention can be implemented as a computer program product with a program code, the program code being operative for performing one of the methods when the computer program product runs on a computer. The program code may for example be stored on a machine readable carrier.

(40) Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine readable carrier.

(41) In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.

(42) A further embodiment of the inventive methods is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. The data carrier, the digital storage medium or the recorded medium are typically tangible and/or non-transitionary.

(43) A further embodiment of the inventive method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may for example be configured to be transferred via a data communication connection, for example via the Internet.

(44) A further embodiment comprises a processing means, for example a computer, or a programmable logic device, configured to or adapted to perform one of the methods described herein.

(45) A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein.

(46) A further embodiment according to the invention comprises an apparatus or a system configured to transfer (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may, for example, be a computer, a mobile device, a memory device or the like. The apparatus or system may, for example, comprise a file server for transferring the computer program to the receiver.

(47) In some embodiments, a programmable logic device (for example a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods may be performed by any hardware apparatus.

(48) The apparatus described herein may be implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer.

(49) The methods described herein may be performed using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer.

(50) The above described embodiments are merely illustrative for the principles of the present invention. It is understood that modifications and variations of the arrangements and the details described herein will be apparent to others skilled in the art. It is the intent, therefore, to be limited only by the scope of the impending patent claims and not by the specific details presented by way of description and explanation of the embodiments herein.

(51) While this invention has been described in terms of several embodiments, there are alterations, permutations, and equivalents which fall within the scope of this invention. It should also be noted that there are many alternative ways of implementing the methods and compositions of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, permutations and equivalents as fall within the true spirit and scope of the present invention.