US5764698A — Method and apparatus for efficient compression of…

Claim 1

Independent Claim 121 words

A method in a data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said method comprising: separating each of said plurality of samples into a plurality of subbands; predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 2

Independent Claim 121 words

A method in a data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said method comprising: separating each of said plurality of samples into a plurality of subbands; predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 3

Dependent Claim 72 words

The method of claim 1, wherein said step of predicting a signal to mask ratio includes predicting said signal to mask ratio as follows: ##EQU7## wherein y i is a signal to mask ratio for subband i,j is the sample frame, N is a number of sample frames, β i ,j is a prediction coefficient, β i ,33 is a bias coefficient, and x j is an energy value for subband i.

Claim 4

Dependent Claim 59 words

The method of claim 2 further comprising ascertaining prediction coefficients as follows: ##EQU8## wherein Y k (j) is a signal to mask ratio for a subband k at same frame j,k is a subband number, j is a frame number, N is a number of frames, ε k (j) is a modeling error for subband k at frame j.

Claim 5

Dependent Claim 16 words

The method of claim 3 further comprising acquiring signal to mask ratios from a psychoacoustic model.

Claim 6

Dependent Claim 132 words

A data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; prediction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocation means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantization means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 7

Dependent Claim 132 words

A data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; prediction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocation means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantization means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 8

Dependent Claim 70 words

The data processing system of claim 5, wherein said prediction means includes means for predicting said signal to mask ratio as follows: ##EQU9## wherein y i is a signal to mask ratio for subband i,j is the sample frame, N is a number of sample frames, β i ,j is a prediction coefficient, β i ,33 is a bias coefficient, and x j is an energy value for subband i.

Claim 9

Dependent Claim 63 words

The data processing system of claim 6 further comprising means for ascertaining prediction coefficients as follows: ##EQU10## wherein Y k (j) is a signal to mask ratio for a subband k at same frame j,k is a subband number, j is a frame number, N is a number of frames, ε k (j) is a modeling error for subband k at frame j.

Claim 10

Dependent Claim 20 words

The data processing system of claim 7 further comprising means for acquiring signal to mask ratios from a psychoacoustic model.

Claim 11

Dependent Claim 18 words

The data processing system of claim 8, wherein said psychoacoustic model is a psychoacoustic model specified by MPEG.

Claim 12

Dependent Claim 15 words

The data processing system of claim 9, wherein said psychoacoustic model is Psychoacoustic Model 2.

Claim 13

Dependent Claim 17 words

The data processing system of claim 6, wherein x j is a pseudo-energy value for subband j.

Claim 14

Dependent Claim 17 words

The data processing system of claim 6, wherein x j is a squared-energy value for subband j.

Claim 15

Dependent Claim 18 words

The data processing system of claim 6, wherein said data processing system is an IBM RISC SYSTEM/6000 computer.

Claim 16

Dependent Claim 16 words

The data processing system of claim 5, wherein said model is a plurality of prediction coefficients.

Claim 17

Dependent Claim 132 words

A computer program product for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples comprising: first instruction means for separating each of said plurality of samples into a plurality of subbands; second instruction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; third instruction means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and fourth instruction means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 18

Dependent Claim 132 words

A computer program product for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples comprising: first instruction means for separating each of said plurality of samples into a plurality of subbands; second instruction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; third instruction means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and fourth instruction means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 19

Independent Claim 130 words

An apparatus for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; prediction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocation means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantization means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 20

Independent Claim 130 words

An apparatus for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; prediction means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; allocation means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and quantization means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 21

Dependent Claim 68 words

The apparatus of claim 16, wherein said prediction means includes means for predicting said signal to mask ratio as follows: ##EQU11## wherein y i is a signal to mask ratio for subband i,j is the sample frame, N is a number of sample frames, β i ,j is a prediction coefficient, β i ,33 is a bias coefficient, and x j is an energy value for subband i.

Claim 22

Dependent Claim 133 words

A data processing system comprising: a processor; a digital audio source that provides a digital audio signal, wherein said digital audio signal includes a plurality of samples; separation means for separating each of said plurality of samples into a plurality of subbands; processor means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; processor means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and processor means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 23

Dependent Claim 133 words

A data processing system comprising: a processor; a digital audio source that provides a digital audio signal, wherein said digital audio signal includes a plurality of samples; separation means for separating each of said plurality of samples into a plurality of subbands; processor means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of relationships between energy values within each of said plurality of subbands and signal to mask ratios values based on a predetermined psychoacoustic model; processor means for allocating a number of bits in response to said predicted signal to mask ratio and a preselected bit-rate; and processor means for quantizing each of said plurality of subbands based on said number of bits allocated, wherein said digital audio signal may be efficiently compressed.

Claim 24

Dependent Claim 30 words

The data processing system of claim 18, wherein said separation means is a processor including instruction means for separating each of said plurality of samples into a plurality of subbands.

Claim 25

Dependent Claim 72 words

The data processing system of claim 18, wherein said processor means for predicting includes means for predicting said signal to mask ratio as follows: ##EQU12## wherein y i is a signal to mask ratio for subband i,j is the sample frame, N is a number of sample frames, β i ,j is a prediction coefficient, β i ,33 is a bias coefficient, and x j is an energy value for subband i.

Claim 26

Dependent Claim 63 words

The data processing system of claim 20 further comprising means for ascertaining prediction coefficients as follows: ##EQU13## wherein Y k (j) is a signal to mask ratio for a subband k at same frame j,k is a subband number, j is a frame number, N is a number of frames, ε k (j) is a modeling error for subband k at frame j.

Claim 27

Independent Claim 93 words

A method in a data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said method comprising: separating each of said plurality of samples into a plurality of subbands; and predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of the relationships between energy values within each of said plurality of subbands and signal to mask ratio values based on a predetermined psychoacoustic model, wherein said model includes a matrix of prediction coefficients indexed by subbands.

Claim 28

Independent Claim 93 words

A method in a data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said method comprising: separating each of said plurality of samples into a plurality of subbands; and predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of the relationships between energy values within each of said plurality of subbands and signal to mask ratio values based on a predetermined psychoacoustic model, wherein said model includes a matrix of prediction coefficients indexed by subbands.

Claim 29

Dependent Claim 98 words

A data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; and predicting means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of the relationships between energy values within each of said plurality of subbands and signal to mask ratio values based on a predetermined psychoacoustic model, wherein said model includes a matrix of prediction coefficients indexed by subbands.

Claim 30

Dependent Claim 98 words

A data processing system for efficiently compressing a digital audio signal, wherein said digital audio signal includes a plurality of samples, said data processing system comprising: separation means for separating each of said plurality of samples into a plurality of subbands; and predicting means for predicting a signal to mask ratio for each of said plurality of subbands utilizing a model of the relationships between energy values within each of said plurality of subbands and signal to mask ratio values based on a predetermined psychoacoustic model, wherein said model includes a matrix of prediction coefficients indexed by subbands.

Annuity Stage	Window Opens	Payment Deadline	Surcharge Period Until	Estimated Fee	Status
3.5 Years (Year 4)	2001-06-08	2001-12-08	2002-06-09	$2000.00	Window Closed / Lapsed
7.5 Years (Year 8)	2005-06-08	2005-12-08	2006-06-09	$3760.00	Window Closed / Lapsed
11.5 Years (Year 12)	2009-06-08	2009-12-08	2010-06-09	$7700.00	Window Closed / Lapsed

Method and apparatus for efficient compression of high quality digital audio

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