# US 2026/0311706 A1 · Method for performing packet loss concealment in complex filter bank domain

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- Number: US 2026/0311706 A1
- Document ID: US20260311706A1
- Status: Published application
- Kind: A1
- Application number: 19/471,821
- Filed: 2024-03-22
- Published: 2026-10-08
- Earliest claimed: 2023-04-05
- Assignees: Dolby International AB
- Applicants: Dolby International AB
- Inventors: Stefan Bruhn
- Web page: https://patentgrep.com/patent/US20260311706A1

## CPC

- G10L 19/005: Correction of errors induced by the transmission channel, if related to the coding algorithm
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING

## Abstract

The present disclosure relates to a method and system for concealing a lost or corrupt frame of audio content in a sequence of audio frames The method comprises obtaining at least one first frame associated with the frame sequence and identifying whether a second frame, subsequent to the at least one first frame, is valid or invalid. When the second frame is identified as invalid, the method comprises generating a set of Time-Frequency (TF) tile values for a replacement frame to replace the second frame by applying a sinusoidal extension process to generate the set of TF tile values for the replacement frame or applying a linear prediction process to generate the set of TF tile values for the replacement frame based on a degree of tonality of at least one preceding frame.

## Claims

### Claim 1

A method to conceal a lost or corrupt frame with audio content in a frame sequence, the method comprising:
obtaining at least one first frame associated with the frame sequence, the at least one first frame being a frame of the frame sequence or a generated replacement frame;
identifying whether a second frame, subsequent to the at least one first frame, is valid or invalid;
when the second frame is identified as invalid, generating a set of Time-Frequency (TF) tile values for a replacement frame to replace the second frame by:
analyzing the at least one first frame to determine a degree of tonality; and
comparing the degree of tonality to a threshold value to determine if the degree of tonality exceeds the threshold value;
when the degree of tonality exceeds the threshold value, applying a sinusoidal extension process to generate the set of TF tile values for the replacement frame; and
when the degree of tonality does not exceed the threshold value, applying a linear prediction process to generate the set of TF tile values for the replacement frame; and
outputting the replacement frame to replace the second frame.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
when the second frame is identified as valid:
identifying whether the at least one first frame is valid or invalid;
when the at least one first frame is identified as invalid, generating a set of TF tile values for a replacement frame to replace the second frame by:
obtaining an extension set of TF tile values of the at least one first frame;
generating one or more crossfaded TF tile values by crossfading the set of TF tile values of the second frame with the extension set of TF tile values of the at least one first frame in a crossfade region; and
outputting the second frame with the one or more crossfaded TF tile values as the replacement frame to replace the second frame.

### Claim 3 (depends on 2)

The method of claim 2, wherein obtaining the extension set of TF tile values of the at least one first frame comprises:
generating the extension set of TF tile values based on TF tile values of the at least one first frame based on either the sinusoidal extension process or the linear prediction process.

### Claim 4 (depends on 3)

The method of claim 3, wherein each frame comprises N subsequent TF tile values associated with N subsequent samples and wherein the extension set of TF tile values comprises K subsequent TF tile values that span K subsequent samples that are temporally later than the N samples of the first frame.

### Claim 5 (depends on 2)

The method of claim 2, wherein the crossfade region comprises a predetermined number of the temporally earliest TF tile values of the set of TF tile values of the second frame.

### Claim 6 (depends on 2)

The method of claim 2, wherein generating one or more crossfaded TF tile values comprises, for each TF tile values in the crossfade region, calculating a crossfade weighted sum of a TF tile value of the second frame with a TF tile value of the extension set of TF tile values of the at least one first frame.

### Claim 7 (depends on 6)

The method of claim 6, wherein a crossfade weighting factor of the crossfade weighted sum indicates the portion of the crossfade weighted sum that is to be constituted by a TF tile value of the extension set of TF tile values and wherein the weighting factor for subsequent crossfaded TF tile values in the crossfading region decreases for temporally later crossfaded TF tile values.

### Claim 8 (depends on 2)

The method of claim 2, wherein the replacement frame comprises the crossfaded TF tile values in the crossfading region and the replacement frame further comprises a trailing region comprising TF tile values of the second frame being outside the crossfading region.

### Claim 9 (depends on 2)

The method of claim 2, further comprising:
when the degree of tonality for the at least one first frame exceeds the threshold value, calculating extension TF tile values with sinusoidal extension based on at least two TF tile values of the at least one first frame; and
when the degree of tonality for the first frame does not exceed the threshold value, calculating extension TF tile values with the linear prediction process based on at least two TF tile values of the at least one first frame.

### Claim 10

A method to conceal a lost or corrupt frame with audio content in a frame sequence, the method comprising:
obtaining at least one first frame associated with the frame sequence, the at least one first frame being a frame of the frame sequence or a generated replacement frame;
identifying whether a second frame, subsequent to the at least one first frame, is valid or invalid;
when the second frame is identified as invalid, generating a set of Time-Frequency (TF) tile values for a replacement frame to replace the second frame by:
analyzing the at least one first frame to determine a degree of tonality; and
comparing the degree of tonality to a threshold value to determine if the degree of tonality exceeds the threshold value;
when the degree of tonality exceeds the threshold value, applying a sinusoidal extension process to generate the set of TF tile values for the replacement frame; and
when the degree of tonality does not exceed the threshold value, applying a linear prediction process to generate the set of TF tile values for the replacement frame; and
outputting the replacement frame to replace the second frame;
wherein the at least one first frame and the second frame are CQMF frames that each include a set of CQMF samples, wherein each of the CQMF samples comprises at least one TF tile value, wherein generating the set of TF tile values for the replacement frame further comprises:
determining a complex parameter based on at least two TF tile values of different CQMF samples in the at least one first frame; and
generating the set of TF tile values for the replacement frame by modifying a TF tile value of the at least one first frame with the complex parameter.

### Claim 11 (depends on 10)

The method of claim 10, wherein each CQMF sample is a sample of a Complex Low-Delay Filter Bank, CLDFB, representation as specified in the 3GPP Immersive Voice and Audio Services, IVAS, Codec.

### Claim 12 (depends on 10)

The method of claim 10, wherein generating the set of TF tile values for the replacement frame comprises:
generating a first replacement TF tile value in a first CQMF sample of the replacement frame by modifying a TF tile value of the at least one first frame with the complex parameter.

### Claim 13 (depends on 12)

The method of claim 12, wherein generating the set of TF tile values for the replacement frame further comprises:
generating a second replacement TF tile value in a second CQMF sample of the replacement frame, subsequent to or preceding the first CQMF sample of the replacement frame, by modifying the generated first replacement TF tile value of the first CQMF sample in the replacement frame with the complex parameter.

### Claim 14 (depends on 10)

The method of claim 10, further comprising:
determining a vector, the vector comprising N elements with index n ranging from 0 to N−1, wherein each of the N elements is proportional to the complex parameter to the (n+1)-th power; and
wherein generating the set of TF tile values for the replacement frame comprises:
multiplying a TF tile value of the first frame with the vector.

### Claim 15 (depends on 10)

The method of claim 10, wherein the complex parameter includes one or more of a real part, an imaginary part, or both real and imaginary parts.

### Claim 16 (depends on 10)

The method of claim 10, wherein applying the sinusoidal extension process to generate the set of TF tile values for the replacement frame further comprises:
calculating the complex parameter as a complex evolution parameter that parameterize a complex sinusoid based on the at least two TF tile values of different CQMF samples in the at least one first frame, and
wherein generating the set of TF tile values for the replacement frame comprises performing sinusoidal extension based on the complex evolution parameter.

### Claim 17 (depends on 16)

The method of claim 16, wherein calculating the complex evolution parameter comprises:
calculating a phase parameter of the complex evolution parameter as a mean phase difference between TF tile values of a phase context window of TF tile values of the at least one first frame;
optionally generating the set of TF tile values for the replacement frame with the phase parameter;
optionally calculating at least one phase perturbation parameter based on the deviation of the phase of at least one TF tile value in the first frame from the phase parameter; and
optionally adjusting the phase parameter using the phase perturbation parameter prior to generating the set of TF tile values for the replacement frame with the phase parameter.

### Claim 18

(canceled)

### Claim 19

(canceled)

### Claim 20 (depends on 16)

The method of claim 16, wherein calculating the complex evolution parameter comprises:
calculating a magnitude parameter of the complex evolution parameter as a mean magnitude ratio between subsequent TF tile values in a magnitude context window of TF tile values of the at least one first frame;
optionally generating the set of TF tile values for the replacement frame with the magnitude parameter;
optionally determining a magnitude perturbation parameter based on the deviation of the magnitude of at least one TF tile value in the at least one first frame from the magnitude parameter; and
optionally adjusting the magnitude parameter using the magnitude perturbation parameter prior to generating the set of TF tile values for the replacement frame with the magnitude parameter.

### Claim at position 21

21-22. (canceled)

### Claim 23 (depends on 10)

The method of claim 10, wherein applying the linear prediction extension process to generate the set of TF tile values for the replacement frame further comprises:
calculating the complex parameter as at least one complex predictor coefficient of a linear predictor configured to predict a TF tile value in a subsequent CQMF sample in the at least one first frame based on a TF tile value in at least one preceding CQMF sample of the at least one first frame; and
wherein generating the set of TF tile values for the replacement frame comprises performing linear prediction of the set of TF tile values based on the at least one complex predictor coefficient.

### Claim 24 (depends on 23)

The method of claim 23, calculating the complex parameter as at least one complex predictor coefficient comprises:
identifying a first order complex coefficient that is multiplied with a TF tile value of a preceding CQMF sample to predict a TF tile value in a subsequent CQMF sample in a predictor context window of the at least one first frame, wherein the first order complex coefficient is identified by minimizing a prediction error in the predictor context window;
wherein calculating the complex parameter as at least one complex predictor coefficient optionally comprises:
determining a second order complex predictor coefficient that is multiplied with a second preceding TF tile value of a second preceding CQMF sample value to predict the TF tile value in the subsequent COMF sample in the predictor context window, wherein the first and second order predictor coefficients are identified by minimizing the prediction error in the predictor context window.

### Claim 25

(canceled)

### Claim 26 (depends on 23)

The method of claim 23, wherein applying the linear prediction process to generate the set of TF tile values for the replacement frame comprises:
generating a predicted set of TF tile values with the at least one complex predictor coefficient;
forming a set of modified TF tile value as a weighted sum of the predicted set of TF tile values and a set of TF tile values of the at least one first frame; and
forming the replacement frame based on the set of modified TF tile values;
wherein optionally a weighting factor of the weighted sum is based on a magnitude of the at least one complex predictor coefficient;
wherein optionally a first weighting factor for a first modified TF tile value differs from a second weighting factor of a second modified TF tile value such that the ratio between the first and second weighting factors is equal to the magnitude of the at least one complex predictor coefficient; and
wherein optionally the replacement frame comprises the set of modified TF tile values in a decay region and the replacement frame further comprises a repetition region comprising unmodified TF tile values of the first frame, wherein the decay region is temporally earlier than the repetition region.

### Claim at position 26

27-29. (canceled)

### Claim 30 (depends on 10)

The method of claim 10, wherein analyzing the at least one first frame to determine the degree of tonality comprises:
evaluating TF tile values of the at least one first frame to identify differences in phase between different TF tile values;
calculating a phase standard deviation based on the identified differences in phase between different TF tile values; and
comparing the phase standard deviation to a phase threshold to determine the at least one first frame is tonal when the phase standard deviation is below the phase threshold, and to determine the at least one first frame is noise-like when the phase standard deviation is equal to or above than the phase threshold.

### Claim at position 28

31-44. (canceled)