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.

Authors: Nam, Woo Hyun; Lee, Tammy; Ko, Sang Chul; Son, Yoonjae; Chung, Hyun Kwon; Kim, Kyung-Rae; Kim, Jungkyu; Hwang, Sunghee; Lee, Kyunggeun
Affiliation: Samsung Research, Samsung Electronics, Seoul, Republic of Korea
AES Convention: 151 (October 2021) Paper Number: 10525
Publication Date: October 13, 2021 Import into BibTeX
Subject: Multichannel and spatial audio processing and applications
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=21489

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:   /conv/151/10525.pdf

Start a discussion about this paper!