Geometrically-Motivated Primary-Ambient Decomposition With Center-Channel Extraction

TL;DR

This paper introduces a geometrically-motivated primary-ambient decomposition method that enhances stereo to surround sound up-mixing, significantly improving user satisfaction in listening tests.

Contribution

It presents a novel two-step approach combining signal-adaptive rotations and center-channel extraction for primary-ambient separation in stereo audio.

Findings

Enhanced surround sound up-mixing from stereo signals

Significant increase in user satisfaction in listening tests

Effective primary-ambient separation using the proposed method

Abstract

A geometrically-motivated method for primary-ambient decomposition is proposed and evaluated in an up-mixing application. The method consists of two steps, accommodating a particularly intuitive explanation. The first step consists of signal-adaptive rotations applied on the input stereo scene, which translate the primary sound sources into the center of the rotated scene. The second step applies a center-channel extraction method, based on a simple signal model and optimal in the mean-squared-error sense. The performance is evaluated by using the estimated ambient component to enable surround sound starting from real-world stereo signals. The participants in the reported listening test are asked to adjust the audio scene envelopment and find the audio settings that pleases them the most. The possibility for up-mixing enabled by the proposed method is used extensively, and the user satisfaction is significantly increased compared to the original stereo mix.