Enhanced chroma extraction from an audio codec

1. A method for processing a block of samples of an audio signal, the method being performed at a spectral band replication based audio encoder which includes a core encoder adapted to derive a block of frequency coefficients from the block of samples of the audio signal and to generate an encoded bitstream of the audio signal from the block of frequency coefficients, and the method comprising:

receiving the block of frequency coefficients from the core encoder of the spectral band replication based audio encoder;

determining a chroma vector for the block of samples of the audio signal based on the received block of frequency coefficients, wherein determining the chroma vector comprises applying frequency dependent psychoacoustic processing to the received block of frequency coefficients or to one or more frequency coefficients which are determined on the basis of the received block of frequency coefficients;

determining melodic and/or harmonic content of the block of samples of the audio signal based on the chroma vector for the block of samples of the audio signal; and

storing the melodic and/or harmonic content on media or transferring the melodic and/or harmonic content via a network.

2. The method of claim 1 , wherein

the block of samples of the audio signal comprises N succeeding short-blocks of M samples each, respectively;

the received block of frequency coefficients comprises N corresponding short-blocks of M frequency coefficients each, respectively, and wherein the method further comprises:

estimating a long-block of frequency coefficients corresponding to the block of samples of the audio signal from the N short-blocks of M frequency coefficients; wherein the estimated long-block of frequency coefficients has an increased frequency resolution compared to the N short-blocks of frequency coefficients; and

determining the chroma vector for the block of samples of the audio signal based on the estimated long-block of frequency coefficients.

3. The method of claim 2 , wherein estimating the long-block of frequency coefficients comprises interleaving corresponding frequency coefficients of the N short-blocks of frequency coefficients, thereby yielding an interleaved long-block of frequency coefficients.

4. The method of claim 3 , wherein estimating the long-block of frequency coefficients comprises decorrelating the N corresponding frequency coefficients of the N short-blocks of frequency coefficients by applying a transform with energy compaction property to the interleaved long-block of frequency coefficients.

5. The method of claim 2 , wherein estimating the long-block of frequency coefficients comprises:

forming a plurality of sub-sets of the N short-blocks of frequency coefficients; wherein the number of short-blocks per sub-set is selected based on the audio signal;

for each sub-set, interleaving corresponding frequency coefficients of the short-blocks of frequency coefficients, thereby yielding an interleaved intermediate-block of frequency coefficients of the sub-set; and

for each sub-set, applying a transform with energy compaction property, e.g. a DCT-II transform, to the interleaved intermediate-block of frequency coefficients of the sub-set, thereby yielding a plurality of estimated intermediate-blocks of frequency coefficients for the plurality of sub-sets.

6. The method of claim 5 , wherein the frequency dependent psychoacoustic processing is applied to one of the plurality of estimated intermediate-blocks of frequency coefficients.

7. The method of claim 2 , wherein estimating the long-block of frequency coefficients comprises applying a polyphase conversion to the N short-blocks of M frequency coefficients, wherein

the polyphase conversion is based on a conversion matrix for mathematically transforming the N short-blocks of M frequency coefficients to an accurate long-block of N×M frequency coefficients; and

the polyphase conversion makes use of an approximation of the conversion matrix with a fraction of conversion matrix coefficients set to zero.

8. The method of claim 2 , wherein estimating the long-block of frequency coefficients comprises:

forming a plurality of sub-sets of the N short-blocks of frequency coefficients; wherein the number L of short-blocks per sub-set is selected based on the audio signal, L<N;

applying an intermediate polyphase conversion to the plurality of sub-sets, thereby yielding a plurality of estimated intermediate-blocks of frequency coefficients;

wherein the intermediate polyphase conversion is based on an intermediate conversion matrix for mathematically transforming L short-blocks of M frequency coefficients to an accurate intermediate-block of L×M frequency coefficients; and wherein the intermediate polyphase conversion makes use of an approximation of the intermediate conversion matrix with a fraction of intermediate conversion matrix coefficients set to zero.

9. The method of claim 2 , further comprising:

estimating a super long-block of frequency coefficients corresponding to a plurality of blocks of samples from a corresponding plurality of long-blocks of frequency coefficients; wherein the estimated super long-block of frequency coefficients has an increased frequency resolution compared to the plurality of long-blocks of frequency coefficients.

10. The method of claim 9 , wherein the frequency dependent psychoacoustic processing is applied to the estimated super long-block of frequency coefficients.

11. The method of claim 2 , wherein the frequency dependent psychoacoustic processing is applied to the estimated long-block of frequency coefficients.

12. The method of claim 1 , wherein applying frequency dependent psychoacoustic processing comprises:

comparing a value derived from at least one frequency coefficient of the received block of frequency coefficients or from at least one frequency coefficient being determined on the basis of the received block of frequency coefficients to a frequency dependent energy threshold; and

setting the frequency coefficient to zero if the frequency coefficient is below the energy threshold.

13. The method of claim 12 , wherein the derived value corresponds to an average energy derived from a plurality of frequency coefficients for a corresponding plurality of frequencies.

14. The method of claim 1 , wherein determining the chroma vector comprises:

classifying plural frequency coefficients of the received block of frequency coefficients or being determined on the basis of the received block of frequency coefficients to tone classes of the chroma vector; and

determining cumulated energies for the tone classes of the chroma vector based on the classified frequency coefficients.

15. An audio encoder adapted to encode an audio signal, the audio encoder comprising:

a core encoder adapted to encode a downsampled component of the audio signal, wherein the core encoder is adapted to encode a block of samples of the downsampled component of the audio signal by transforming the block of samples of the downsampled component of the audio signal from the time domain into the frequency domain, thereby yielding a corresponding block of frequency coefficients in the frequency domain; and

a processor adapted to determine a chroma vector of the block of samples of the downsampled component of the audio signal based on the block of frequency coefficients received from the core encoder, wherein the processor is further adapted to determine the chroma vector by applying frequency dependent psychoacoustic processing to the received block of frequency coefficients or to one or more frequency coefficients which are determined on the basis of the received block of frequency coefficients; wherein the chroma vector of the block of samples of the audio signal is indicative of melodic and/or harmonic content of the block of samples of the audio signal; wherein the melodic and/or harmonic content is to be stored on media or transferred via a network.

16. The encoder of claim 15 , further comprising a spectral band replication encoder adapted to encode a corresponding high frequency component of the audio signal and also comprising a multiplexer adapted to generate an encoded bitstream from data provided by the core encoder and the spectral band replication encoder, wherein the multiplexer is adapted to add information derived from the chroma vector as metadata to the encoded bitstream.

17. An audio decoder adapted to decode an audio signal,

the audio decoder being adapted to receive an encoded bitstream and adapted to extract a block of frequency coefficients from the encoded bitstream;

wherein the extracted block of frequency coefficients is associated with a corresponding block of samples of a downsampled component of the audio signal; and

the audio decoder comprising:

a processor adapted to determine a chroma vector of the block of samples of the audio signal based on the extracted block of frequency coefficients, wherein the processor is further adapted to determine the chroma vector by applying frequency dependent psychoacoustic processing to the extracted block of frequency coefficients or to one or more frequency coefficients which are determined on the basis of the extracted block of frequency coefficients; wherein the processor is further adapted to determine melodic and/or harmonic content of the block of samples of the audio signal based on the chroma vector for the block of samples of the audio signal; wherein the melodic and/or harmonic content is to be stored on media or transferred via a network.

18. A non-transitory computer readable medium storing a software program adapted for execution on a processor and for performing the method steps of claim 1 when carried out on the processor.

19. A computer program product including a non-transitory computer readable medium comprising executable instructions for performing the method steps of claim 1 when executed on a computer.