公开(公告)号：US12223970B2

公开(公告)日：2025-02-11

申请号：US18103993

申请日：2023-01-31

Applicant: Electronics and Telecommunications Research Institute

Inventor： Jongmo Sung ,  Seung Kwon Beack ,  Tae Jin Lee ,  Woo-taek Lim ,  Inseon Jang ,  Byeongho Cho

IPC: G10L19/087 ,  G10L19/038 ,  G10L19/13 ,  G10L25/30 ,  G10L19/02

Abstract: An encoding method, a decoding method, an encoder for performing the encoding method, and a decoder for performing the decoding method are provided. The encoding method includes outputting LP coefficients bitstream and a residual signal by performing an LP analysis on an input signal, outputting a first latent signal obtained by encoding a periodic component of the residual signal, a second latent signal obtained by encoding a non-periodic component of the residual signal, and a weight vector for each of the first latent signal and the second latent signal, using a first neural network module, and outputting a first bitstream obtained by quantizing the first latent signal, a second bitstream obtained by quantizing the second latent signal, and a weight bitstream obtained by quantizing the weight vector, using a quantization module.

公开(公告)号：US12223426B2

公开(公告)日：2025-02-11

申请号：US18166407

申请日：2023-02-08

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE ,  YONSEI UNIVERSITY WONJU INDUSTRY-ACADEMIC COOPERATION FOUNDATION

Inventor： Jongmo Sung ,  Seung Kwon Beack ,  Tae Jin Lee ,  Woo-taek Lim ,  Inseon Jang ,  Byeongho Cho ,  Young Cheol Park ,  Joon Byun ,  Seungmin Shin

IPC: G10L19/00 ,  G06N3/08 ,  G10L19/028 ,  G10L19/038 ,  G10L25/30 ,  G10L25/60 ,  G10L25/69 ,  G06N3/084 ,  G10L15/00 ,  G10L19/22

Abstract: Provided is a method and apparatus for designing and testing an audio codec using quantization based on white noise modeling. A neural network-based audio encoder design method includes generating a quantized latent vector and a reconstructed signal corresponding to an input signal by using a white noise modeling-based quantization process, computing a total loss for training a neural network-based audio codec, based on the input signal, the reconstruction signal, and the quantized latent vector, training the neural network-based audio codec by using the total loss, and validating the trained neural network-based audio codec to select the best neural network-based audio codec.