US 11,741,977 B2Granted

Vector quantizer

AssigneeTelefonaktiebolaget L M Ericsson (publ)

InventorsVolodya Grancharov, Tomas Jansson Toftgård

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Abstract

Vector Quantizer and method therein for vector quantization, e.g. in a transform audio codec. The method comprises comparing an input target vector with four centroids C0, C1, C0,flip and C1,flip, wherein centroid C0,flip is a flipped version of centroid C0 and centroid C1,flip is a flipped version of centroid C1, each centroid representing a respective class of codevectors. A starting point for a search related to the input target vector in the codebook is determined, based on the comparison. A search is performed in the codebook, starting at the determined starting point, and a codevector is identified to represent the input target vector. A number of input target vectors per block or time segment is variable. A search space is dynamically adjusted to the number of input target vectors. The codevectors are sorted according to a distortion measure reflecting the distance between each codevector and the centroids C0 and C1.

Claims20

Dependent claims

A method performed by a transform codec comprising a vector quantizer, the method comprising:

obtaining a number of input target vectors, wherein the number of input target vectors per time segment is variable and said number of input target vectors comprise coefficients derived from an audio signal or a video signal;
comparing an input target vector of the number of input target vectors with at least two centroids C0, C1, to determine which of the at least two centroids to assign the input target vector to, each centroid representing a respective class of codevectors;
determining a starting point in a codebook for a search related to the input target vector based on which of the at least two centroids the input target vector was determined to be assigned the input target vector, wherein a search space for the search is dynamically adjusted based on the number of input target vectors obtained and a computational complexity constraint, and each codevector in a respective class of codevectors is sorted according to a distortion measure reflecting a distance between the codevector and said at least two centroids C0 and C1;
performing the search in the codebook starting at the starting point determined, and identifying a codevector to represent the input target vector;
and
performing an action based on the codevector identified.

3 more elements

A transform codec comprising a vector quantizer comprising:

a communication unit, adapted to obtain a number of input target vectors, wherein the number of input target vectors per time segment is variable and said input target vectors comprise coefficients derived from an audio signal or a video signal;
a comparing unit, adapted to, for an input target vector of the number of input target vectors, compare the input target vector with at least two centroids C0, C1, to determine which of the at least two centroids to assign the input target vector to, each centroid representing a respective class of codevectors;
a determining unit adapted to determine a starting point in a codebook, for the input target vector, for a search in the codebook, based which of the at least two centroids the input target vector was determined to be assigned the input target vector and to dynamically adjust a search space based on the number of input target vectors obtained and a computational complexity constraint;
a search unit, adapted to, for the input target vector, perform a search in the codebook starting at the starting point determined, and identify a codevector to represent the input target vector, wherein each codevector in a respective class of codevectors is sorted according to a distortion measure reflecting a distance between the codevector and said at least two centroids C0 and C1;
and
a providing unit, adapted to perform an action based on the codevector identified.

3 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/236,563Filed 21 Apr 2021 · continuation
Priority: 29 Mar 2012
Published: US 2021/0241779 A15 Aug 2021
Granted: 29 Aug 2023
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

G10L 19/038
Quantisation or dequantisation of spectral components: vector quantisation, e.g. TwinVQ audio
G10L 19/18
Vocoder architecture: vocoders using multiple modes
H03M 7/3082
Compression ; Expansion; Suppression of unnecessary data, e.g. redundancy reduction: vector coding
H04N 19/94
Using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals: vector quantisation

Family

Application61/617,151Us provisional application · filed 29 Mar 2012
PCT/SE2012/051381Parent of this continuation · filed 12 Dec 2012
Application15/187,943Parent of this continuation · filed 21 Jun 2016
US 9,401,155 B2Parent of this continuation · filed 26 Jul 2016
Application15/805,768Parent of this continuation · filed 7 Nov 2017
US 9,842,601 B2Parent of this continuation · filed 12 Dec 2017
Application16/549,270Parent of this continuation · filed 23 Aug 2019
US 10,468,044 B2Parent of this continuation · filed 5 Nov 2019
US 2021/0241779 A1Pre-grant publication · published 5 Aug 2021
US 11,017,786 B2Parent of this continuation
Application14/387,716Parent of this continuation
US 2015/0051907 A1Published application
US 2016/0300581 A1Published application
US 2018/0061429 A1Published application
US 2019/0378526 A1Published application
US 11,741,977 B2This patent

From the US filing history. Foreign family members aren’t listed.