Effective deployment of temporal noise shaping (TNS) filters
In the MPEG2 Advanced Audio Coder (AAC) standard, Temporal Noise Shaping (TNS) is currently implemented by defining one filter for a given frequency band, and then switching to another filter for the adjacent frequency band when the signal structure in the adjacent band is different than the one in the previous band. The AAC standard limits the number of filters used to either one filter for a “short” block or three filters for a “long” block. In cases where the need for additional filters is present but the limit of permissible filters has been reached, the remaining frequency spectra are simply not covered by TNS. This current practice is not an effective way of deploying TNS filters for most audio signals. We propose two solutions to deploy TNS filters in order to get the entire spectrum of the signal into TNS. The first method involves a filter bridging technique and complies with the current AAC standard. The second method involves a filter clustering technique. Although the second method is both more efficient and accurate in capturing the temporal structure of the time signal, it is not AAC standard compliant. Thus, a new syntax for packing filter information derived using the second method for transmission to a receiver is also outlined.
1. A method of using filters for processing audio signals, comprising:
calculating a filter for each of a plurality of frequency bands;
comparing coefficients of filters in adjacent frequency bands to identify a pair of filters with a shortest Euclidean distance between coefficients;
merging said pair of filters;
repeating all previously recited acts until a predetermined number of total filters is reached;
after said predetermined number of filters is reached, recalculating at least one of said filters using only those frequencies corresponding to a strongest signal within a frequency range covered by said at least one of said filters;
using said recalculated filter for an entire extent of said frequency range; and
processing audio signals using the merged pair of filters.
2. The method of claim 1 , wherein said coefficients are PARCOR coefficients.
3. The method of claim 1 , wherein said merging involves calculating a new filter for a frequency band comprising said adjacent frequency bands of said filters with said shortest Euclidean distance.
4. The method of claim 1 , wherein said strongest signal is identified based on energy/bin within said frequency range.
5. A method of using a filter to process audio signals, comprising:
determining a first filter for a first frequency range;
determining a second filter for a second frequency range, said second frequency range including said first frequency range;
calculating a first Euclidean distance between the coefficients of said first filter and a null set of coefficients;
calculating a second Euclidean distance between the coefficients of said first filter and coefficients of said second filter;
calculating a first prediction gain using said first filter;
calculating a second prediction gain between said first filter and said second filter;
if said second Euclidean distance is greater than said first Euclidean distance and said second prediction gain is less than said first prediction gain, then deploying said first filter for said first frequency range and if said second Euclidean distance is not greater than said first Euclidean distance or said second prediction gain is not less than said prediction gain, then:
recalculating the second Euclidean distance between coefficients of said first filter and coefficients of said second filter;
recalculating the second prediction gain between said first filter and said second filter;
redetermining whether the second Euclidean distance is greater than said first Euclidean distance and said second prediction gain is less than said first prediction gain; and
processing an audio signal using the first filter for the first frequency range.
6. The method of claim 5 , wherein said first and second filters are TNS filters.
7. The method of claim 5 , wherein said coefficients are PARCOR coefficients.
8. The method of claim 5 , further comprising:
if said second Euclidean distance is not greater than said first Euclidean distance or said second prediction gain is not less than said prediction gain, then performing, prior to recalculating the second prediction gain between said first filter and said second filter and recalculating the second Euclidean distance between coefficients of said first filter and coefficients of said second filter:
setting said first filter to equal said second filter;
setting said first Euclidean distance to equal said second Euclidean distance;
setting said first prediction gain to equal said second prediction gain; and
re-determining the second filter for a new frequency range.
9. A method of using a filter for processing audio signals, comprising:
calculating a first Euclidean distance between coefficients of a second filter and coefficients of a first filter, the second filter having a second frequency range including a first frequency range of the first filter;
calculating a second Euclidean distance between the coefficients of said second filter and coefficients of a third filter, the third filter having a third frequency range including the second frequency range;
calculating a first prediction gain between said first filter and said second filter;
calculating a second prediction gain between said second filter and said third filter;
if said second Euclidean distance is greater than said first Euclidean distance and said second prediction gain is less than said first prediction gain, then deploying said second filter for said second frequency range; and
processing an audio signal using the deployed second filter for said second frequency range.