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Convention Paper

AI 3D immersive audio codec based on content-adaptive dynamic down-mixing and up-mixing framework

Authors: Nam, Woo Hyun; Lee, Tammy; Ko, Sang Chul; Son, Yoonjae; Chung, Hyun Kwon; Kim, Kyung-Rae; Kim, Jungkyu; Hwang, Sunghee; Lee, Kyunggeun

AES Convention 151 · Paper 10525 · October 2021

Abstract

Recently, people who prefer to consume media contents via over the top (OTT) platform, such as YouTube, Netflix etc., rather than a conventional broadcasting get increased more and more. To deliver an immersive audio experience to them more effectively, we propose a unified framework for AI-based 3D immersive audio codec. In this framework, to maximize the original immersiveness even at a down-mixed audio, while enabling to precisely reproduce the original 3D audio from the down-mixed audio, content-adaptive dynamic down-mixing and up-mixing scheme is newly proposed. The experimental results show that the proposed framework can render more improved down-mixed audio compared to the conventional method as well as successfully reproduce the original 3D audio.

Details

Published in
AES Convention 151
AES Convention
151
Paper number
10525
Publication date
October 6, 2021
Session subject
Multichannel and spatial audio processing and applications
Affiliation
Samsung Research, Samsung Electronics, Seoul, Republic of Korea (See document for exact affiliation information.)
Type
Convention Paper