IP Library › Granted Patent US 11,456,001
Granted Patent B2
US 11,456,001 · App. 16/814,103 · Granted Sep 27, 2022

Method of encoding high band of audio and method of decoding high band of audio, and encoder and decoder for performing the methods

Inventors: Seung Kwon Beack (Daejeon, KR); Jongmo Sung (Daejeon, KR); Mi Suk Lee (Daejeon, KR); Tae Jin Lee (Daejeon, KR); Hochong Park (Seongnam-si, KR)
Assignees: Electronics and Telecommunications Research Institute; KWANGWOON UNIVERSITY INDUSTRY-ACADEMIC COLLABORATION FOUNDATION
G10L19/0204G06N3/0454G10L19/032G10L21/038
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Quick Facts
Patent No.
US 11,456,001
App. No.
16/814,103
Granted
Sep 27, 2022
Kind
B2
Abstract

Disclosed are a method of encoding a high band of an audio, a method of decoding a high band of an audio, and an encoder and a decoder for performing the methods. The method of decoding a high band of an audio, the method performed by a decoder, includes identifying a parameter extracted through a first neural network, identifying side information extracted through a second neural network, and restoring a high band of an audio by applying the parameter and the side information to a third neural network.

Claims (24)

1. A method of decoding a high band of an audio, the method performed by a decoder, the method comprising:

identifying a parameter extracted through a first neural network;

identifying side information extracted through a second neural network; and

restoring a high band of an audio by applying the parameter and the side information to a third neural network,

wherein, when a decoding frame of the audio is a current frame and there is at least one previous frame with respect to the current frame, a first input applied to the first neural network includes a high-band coefficient of the current frame, and a second input applied to the second neural network includes a high-band coefficient and a low-band coefficient of the previous frame, and a low-band coefficient of the current frame.

2. The method of claim 1 , wherein the first neural network is configured to extract the parameter of the high band from a first input based on a per-frame spectrum of the audio.

3. The method of claim 2 , wherein the first input is determined to be a subset of a spectrum, and

the spectrum includes a high-band coefficient and a low-band coefficient of a previous frame, and a high-band coefficient and a low-band coefficient of a current frame.

4. The method of claim 1 , wherein the second neural network is configured to extract the side information to restore the high band from a second input based on a per-frame spectrum of the audio.

5. The method of claim 4 , wherein the second input is determined to be a subset of a spectrum, and

the spectrum includes a high-band coefficient and a low-band coefficient of a previous frame, and a low-band coefficient of a current frame.

6. The method of claim 1 , wherein, when a decoding frame of the audio is a current frame, a first input applied to the first neural network includes a high-band coefficient of the current frame, and a second input applied to the second neural network includes a low-band coefficient of the current frame.

7. The method of claim 1 , wherein, when a decoding frame of the audio is a previous frame and there is at least one previous frame with respect to a current frame, a first input applied to the first neural network includes a high-band coefficient of the current frame and a high-band coefficient of the previous frame, and a second input applied to the second neural network includes a low-band coefficient of the previous frame.

8. The method of claim 1 , wherein the identifying of the parameter comprises identifying the parameter by dequantizing a quantized parameter received from an encoder.

9. The method of claim 1 , wherein the identifying of the parameter comprises identifying the extracted parameter by randomly sampling an output of the first neural network.

10. The method of claim 1 , wherein the restoring comprises using a high band of the current frame and a high band of at least one previous frame of the current frame.

11. A decoder, comprising:

a processor,

wherein the processor is configured to identify a parameter extracted through a first neural network, identify side information extracted through a second neural network, and restore a high band of an audio by applying the parameter and the side information to a third neural network, and

wherein, when a decoding frame of the audio is a current frame and there is at least one previous frame with respect to the current frame, a first input applied to the first neural network includes a high-band coefficient of the current frame, and a second input applied to the second neural network includes a high-band coefficient and a low-band coefficient of the previous frame, and a low-band coefficient of the current frame.

12. The decoder of claim 11 , wherein the first neural network is configured to extract the parameter of the high band from a first input based on a per-frame spectrum of the audio.

13. The decoder of claim 12 , wherein the first input is determined to be a subset of a spectrum, and

the spectrum includes a high-band coefficient and a low-band coefficient of a previous frame, and a high-band coefficient and a low-band coefficient of a current frame.

14. The decoder of claim 11 , wherein the second neural network is configured to extract the side information to restore the high band from a second input based on a per-frame spectrum of the audio.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 10, 2020
From: BEACK, SEUNG KWON; SUNG, JONGMO; LEE, MI SUK; LEE, TAE JIN; PARK, HOCHONG
To: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE; KWANGWOON UNIVERSITY INDUSTRY-ACADEMIC COLLABORATION FOUNDATION
Reel/Frame 052134/0152 →
Priority Claims (1)
KR 10-2019-0079377 · Jul 2, 2019 · national
Continuity (1)
Related Publication 20210005209A1 · Jan 7, 2021