System and method for masking quantization noise of audio signals

• US 6,058,362 A
• Filed: 06/30/1998
• Issued: 05/02/2000
• Est. Priority Date: 05/27/1998
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Malvar, Henrique S.
• Primary Examiner(s): Dorvil, Richemond
• Application Number:
  US09/107,824
• Time in Patent Office: 672 Days
• Field of Search: 704/200, 704/229, 704/230, 704/226, 704/500, 704/211, 704/201, 704/503, 704/501, 704/502, 341/110, 341/140
• US Class Current: 704/230
• CPC Class Codes: G10L 19/0212 using orthogonal transformation
• CPC Class Codes: G10L 19/24 Variable rate codecs, e.g. for generating different qualities using a scalable representation such as hierarchical encoding or layered encoding

Abstract

The coder/decoder (codec) system of the present invention includes a coder and a decoder. The coder includes a multi-resolution transform processor, such as a modulated lapped transform (MLT) transform processor, a weighting processor, a uniform quantizer, a masking threshold spectrum processor, an entropy encoder, and a communication device, such as a multiplexor (MUX) for multiplexing (combining) signals received from the above components for transmission over a single medium. The decoder comprises inverse components of the encoder, such as an inverse multi-resolution transform processor, an inverse weighting processor, an inverse uniform quantizer, an inverse masking threshold spectrum processor, an inverse entropy encoder, and an inverse MUX. With these components, the present invention is capable of performing resolution switching, spectral weighting, digital encoding, and parametric modeling.

Claims

1. A method for masking quantization noise by spectrally weighting transform coefficients of an input signal having a given bandwidth and produced by a transform processor, comprising:

calculating a masking spectral threshold in a quasi-logarithmic scale that approximates critical bands of a hearing model by applying triangular decays to spectral peaks;

computing plural spread masking thresholds in each critical band as a maximum of contributions from the triangular decays; and

adjusting the spread masking thresholds to produce an absolute threshold.

2. The method of claim 1, wherein calculating a masking spectral threshold comprises:

defining subband upper frequency limits of the quasi-logarithmic scale;

computing plural spectral powers of the quasi-logarithmic scale by averaging signal power for all subbands; and

computing an in-band masking threshold.

3. The method of claim 1, wherein computing plural spread masking thresholds comprise:

considering lateral masking across the critical bands; and

calculating a maximum threshold by convolving spectral values of the quasi-logarithmic scale with triangular decay.

4. The method of claim 3, wherein calculating the maximum threshold comprises calculating a threshold generated by convolving all Bark spectral values with a triangular decay.

5. The method of claim 4, wherein the triangular decay is -25 dB/Bark spreading into lower frequencies and +10 dB/Bark spreading into higher frequencies.

6. The method of claim 1, wherein adjusting the masking thresholds comprises comparing values of the spread masking thresholds with values of a model threshold, wherein a highest value is utilized for all subbands.

7. The method of claim 1, wherein computing plural spread masking thresholds in each critical band as a maximum of contributions from neighboring critical bands comprises initializing a lower frequency spreading limit with a maximum value represented by convolved spectral values with a triangular decay and iteratively resetting the lower frequency spreading limit and a higher frequency spreading limit until a desired number of subbands are covered by the signal bandwidth.

8. The method of claim 1, wherein the plural spread masking thresholds are spread Bark thresholds with Bark subbands and wherein adjusting the spread masking thresholds to produce an absolute threshold comprises comparing the spread Bark thresholds with absolute Fletcher-Munson thresholds to determine a higher value and using the higher value for all Bark subbands.

9. The method of claim 8, wherein the spread Bark thresholds are vector quantized to a predetermined precision level and differentially encoded at a predefined bit per threshold level.

10. The method of claim 9, wherein up to 25 blocks of the Bark thresholds are quantized and wherein the precision level is set to 2.5 dB and the bit per threshold level is set within a range of 2 to 4 bits per threshold value.

11. A noise masking device stored on computer readable memory of a computer system for masking quantization noise by spectrally weighting transform coefficients of an input audio signal having a given bandwidth and produced by a transform processor, comprising:

a threshold processor for calculating a masking spectral threshold in a quasi-logarithmic scale that approximates critical bands of a hearing model by applying triangular decays to spectral peaks;

a spread processor for computing plural spread masking thresholds in each critical band as a maximum of contributions from the triangle decays; and

an adjustment module for adjusting the spread masking thresholds to produce an absolute threshold for efficiently masking unwanted noise of the audio signal.

12. The noise masking device of claim 11, wherein the threshold processor comprises:

a define subband module for defining subband upper frequency limits of the quasi-logarithmic scale;

a compute module for calculating plural spectral powers of the quasi-logarithmic scale by averaging signal power for all subbands and for computing an in-band masking threshold.

13. The noise masking device of claim 11, wherein the spread processor comprises:

a lateral mask module for considering lateral masking across the critical bands; and

a convolve module for calculating a maximum threshold by convolving spectral values of the quasi-logarithmic scale with triangular decay.

14. The noise masking device of claim 13, wherein the convolve module comprises a Bark submodule for calculating a threshold generated by convolving all Bark spectral values with a triangular decay.

15. The noise masking device of claim 14, wherein the triangular decay is -25 dB/Bark spreading into lower frequencies and +10 dB/Bark spreading into higher frequencies.

16. The noise masking device of claim 11, wherein the adjustment module comprises a submodule for comparing values of the spread masking thresholds with values of a model threshold, wherein a highest value is utilized for all subbands.

17. The noise masking device of claim 11, wherein the spread processor is adapted to initialize a lower frequency spreading limit with a maximum value represented by convolved spectral values with a triangular decay and to iteratively reset the lower frequency spreading limit and a higher frequency spreading limit until a desired number of subbands are covered by the signal bandwidth.

18. The noise masking device of claim 11, wherein the plural spread masking thresholds are spread Bark thresholds with Bark subbands and wherein the adjustment module is adapted to compare the spread Bark thresholds with absolute Fletcher-Munson thresholds to determine a higher value and use the higher value for all Bark subbands.

19. The noise masking device of claim 18, wherein the spread Bark thresholds are vector quantized to a predetermined precision level and differentially encoded at a predefined bit per threshold level.

20. The noise masking device of claim 19, wherein up to 25 blocks of the Bark thresholds are quantized and wherein the precision level is set to 2.5 dB and the bit per threshold level is set within a range of 2 to 4 bits per threshold value. transform coefficients of an input audio signal having a given bandwidth and produced by a transform processor, comprising:

a threshold processor for calculating a masking spectral threshold in a quasi-logarithmic scale that approximates critical bands of a hearing model by applying triangular decays to spectral peaks;

a spread processor for computing plural spread masking thresholds in each critical band as a maximum of contributions from [neighboring critical bands] the triangle decays; and

an adjustment module for adjusting the spread masking thresholds to produce an absolute threshold for efficiently masking unwanted noise of the audio signal.