Transient detection is an important algorithm in perceptual audio codecs that enables adaptation in filterbank resolution to effectively mitigate artifacts in encoded audio signals. We present a curated selection of transient detection methods tailored for audio coding purposes, namely high frequency energy (HFE), block perceptual entropy (BPE), time-frequency spectral flatness measure (TFSFM), and sub-block peak energy (SPE). The methods are then evaluated in a MUSHRA listening test using selected critical materials from the EBU-SQAM dataset. This paper provides insights into perceptual audio coding and paves the way for further optimization in transient detection.

Authors: Fan, Senyuan; Kuo, Emily; Shah, Sneha; Bosi, Marina
Affiliations: Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University; Center for Computer Research in Music and Acoustics (CCRMA), Stanford University(See document for exact affiliation information.)
Express Paper 131; AES Convention 155; October 2023
Publication Date: October 25, 2023 Import into BibTeX
Subject: Signal Processing
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=22285

Download Now (1.6 MB)

This paper is Open Access which means you can download it for free.

Learn more about the AES E-Library

E-Library Location:   /conv/155/131.pdf

Start a discussion about this Signal Processing!