The present invention relates to audio signal encoding, audio signal processing and audio signal decoding, and, in particular, to an apparatus and a method for noise shaping using subspace projections for low-rate coding of speech and audio.

In coding speech at low bit-rates, codecs based on the code excited linear prediction (CELP) paradigm are predominant [1]. These codecs model the spectral envelope using linear predictive coding and the fundamental frequency using long-term prediction. The residual is typically encoded in the time domain using vector codebooks. The main weakness of such codecs is their computational complexity, due to the analysis-by-synthesis loop, which is used for optimizing the perceptual quality of the output.

Motivated by a desire to reduce computational complexity, as well as with the aim of unifying speech and audio coding, recently the trend has shifted towards coding in the frequency domain. Modern speech coding algorithms use frequency domain coding to encode the speech signal with low computational complexity.

To minimize the perceived degradation of the speech signal, they shape the quantization noise using a perceptual model. State-of-the-art codecs further apply uniform quantization and arithmetic coding in a rate-loop to efficiently transmit the signal spectra. For higher bit-rates, this approach offers near-optimal SNR and a high perceptual quality. However, at lower bitrates, the quantization noise is highly correlated to the original signal as parts of the spectrum with low energy are quantized to zero. As a consequence, the decoded (audio) signals often sound muffled.

Modern coders like 3rd Generation Partnership Project (3GPP) Enhanced Voice Service (EVS) and Moving Picture Experts Group (MPEG)-D unified speech and audio coding (USAC) [2], [3] encode the signal using the modified discrete cosine transform (MDCT) [4], [5], where quantization and coding is shaped by an envelope model [6].

This approach avoids the analysis-by-synthesis loop and thus allows coding at a low computational complexity. The magnitude of the quantization noise is shaped by a perceptual model, approximating the auditory masking threshold, such that the perceptual effect of the quantization noise is minimized.

Such codecs use an arithmetic coder which requires a rate-loop such that accuracy is scaled to the available bit-rate, which increases the required computational power significantly, and which is a drawback considering the resource constraints on typical platforms such as mobile phones.

Moreover, the arithmetic coder with uniform quantization at a low bitrate tends to correlate the quantization noise to the original speech signal, whereas it offers near-optimal performance for high bit-rates. This correlation yields an encoded (audio) signal that tends to sound muffled, as higher frequencies are often quantized to zero. Moreover, coding efficiency is reduced with decreasing bit-rates.

Different approaches have been presented to counteract the band limited nature of the encoded speech signal. One paradigm would be bandwidth extension methods, where the spectral magnitudes of higher frequencies are estimated either using side-info or blindly from the lower parts of the spectrum [1]. Thus, only the lower frequency regions of the speech signal are encoded explicitly. Another approach is to counteract the muffled sound of encoded speech by applying noisefilling, which adds artificial noise to the holes in the higher frequencies or by applying dithering [7], [8], [9], [10], [11].

The object of the present invention is to provide improved concepts for audio signal encoding, audio signal processing and audio signal decoding. The object of the present invention is solved by an apparatus according to claim1, by an apparatus according to claim11, by a method according to claim23, by a method according to claim24, and by a computer program according to claim25.

An apparatus for encoding an audio input signal to obtain an encoded audio signal is provided. The apparatus comprises a transformation module configured to transform the audio input signal from an original domain to a transform domain to obtain a transformed audio signal. Moreover, the apparatus comprises an encoding module, configured to quantize the transformed audio signal to obtain a quantized signal, and configured to encode the quantized signal to obtain the encoded audio signal. The transformation module is configured to transform the audio input signal depending on a plurality of predefined power values of quantization noise in the original domain.

Furthermore, an apparatus for decoding an encoded audio signal to obtain a decoded audio signal is provided. The apparatus comprises a decoding module, configured to decode the encoded audio signal to obtain a quantized signal, and configured to dequantize the quantized signal to obtain an intermediate signal, being represented in a transform domain. Moreover, the apparatus comprises a transformation module configured to transform the intermediate signal from the transform domain to an original domain to obtain the decoded audio signal. The transformation module is configured to transform the intermediate signal depending on a plurality of predefined power values of quantization noise in the original domain.

Moreover, a method for encoding an audio input signal to obtain an encoded audio signal is provided. The method comprises:Transforming the audio input signal from an original domain to a transform domain to obtain a transformed audio signal.Quantizing the transformed audio signal to obtain a quantized signal. And:Encoding the quantized signal to obtain the encoded audio signal.

Transforming the audio input signal is conducted depending on a plurality of predefined power values of quantization noise in the original domain.

Furthermore, a method for decoding an encoded audio signal to obtain a decoded audio signal is provided. The method comprises:Decoding the encoded audio signal to obtain a quantized signal.Dequantizing the quantized signal to obtain an intermediate signal, being represented in a transform domain.Transforming the intermediate signal from the transform domain to an original domain to obtain the decoded audio signal.

Transforming the intermediate signal is conducted depending on a plurality of predefined power values of quantization noise in the original domain.

Moreover, a non-transitory computer-readable medium comprising a computer program for implementing the method for encoding when being executed on a computer or signal processor is provided.

In contrast to the state-of-the art, embodiments employ uniform quantization in a sub-space, where the quantization noise can be shaped by choice of the subspace projection. For components exceeding one bit/sample, these transforms are complemented either by an iterative delta-coding scheme or by applying arithmetic coding.

Embodiments provide a modification of dithered quantization and coding approach, combined with a differential one bit quantization scheme that offers computationally efficient coding also with constant bit-rates. Due to dithering, the resulting quantization reduces the correlation between quantization noise and the original speech signal and can be shaped according to a perceptual model. Thus, the quantized signal does not lack energy in the higher frequencies and will not sound muffled. Since perceptual quantization noise would then be perceivable at low-energy parts of the spectrum, such as the high-frequencies, one may, e.g., further incorporate Wiener filtering in the decoder to best recover the original signal.

Experiments show that the proposed coder gives a better signal-to-noise ratio (SNR) than conventional uniform quantization with arithmetic coding at low bit-rates and that the coder according to embodiments is very close to optimal coding efficiency. In particular, experiments show that when only iterative one-bit coding is employed, the perceptual SNR is only improved for lower bit-rates. However, the hybrid approach according to embodiments which combines the proposed sub-space transforms with arithmetic coding improves both SNR and perceptual quality for lower bit-rates and converges to the performance of the arithmetic coder at higher bit-rates.

Some embodiments provide a sub space transform, that allows to determine the power spectral density (PSD) of the quantization noise in order to minimize the perceptual degradation.

This subspace transform is applicable, if the required accuracy of each sample is smaller than one bit. Thus, in practice it may, for example, be complemented by a second quantization scheme.

In order to stay in the paradigm of one bit quantization, a combination of the provided subspace transform and a differential one-bit quantization approach may, e.g., be implemented.

Such embodiments iteratively quantize the error of the previous quantization step.

Moreover, in some embodiments, a combination of arithmetic coding and the sub-space transform is provided. In the evaluation the two of the new embodiments are compared to classic arithmetic coding and to a hybrid coder.

In the evaluation some of the embodiments are compared with state-of-the-art methods in a simplified TCX-type coding scenario. The objective evaluation showed that the performance of the provided embodiments of arithmetic coding and the sub-space transform exceeds the performance of the other tested approaches in terms of SNR. The differential approach works particularly well for lower bit-rates. The MUSHRA listening test confirms that the results of the objective evaluation.

Embodiments provide a hybrid coding scheme which exceeds the performance of state-of-the-art encoding schemes both in the objective and in the subjective evaluation. Moreover, the provided embodiments can be readily used in any TCX-like speech coder.

