Audio signal representations for indexing in the transform domain

Emmanuel Ravelli, Gaël Richard, Laurent Daudet

Research output: Contribution to journalArticlepeer-review

Abstract

Indexing audio signals directly in the transform domain can potentially save a significant amount of computation when working on a large database of signals stored in a lossy compression format, without having to fully decode the signals. Here, we show that the representations used in standard transform-based audio codecs (e.g., MDCT for AAC, or hybrid PQF/MDCT for MP3) have a sufficient time resolution for some rhythmic features, but a poor frequency resolution, which prevents their use in tonality-related applications. Alternatively, a recently developed audio codec based on a sparse multi-scale MDCT transform has a good resolution both for time- and frequency-domain features. We show that this new audio codec allows efficient transform-domain audio indexing for three different applications, namely beat tracking, chord recognition, and musical genre classification. We compare results obtained with this new audio codec and the two standard MP3 and AAC codecs, in terms of performance and computation time.

Original languageEnglish
Article number5410060
Pages (from-to)434-446
Number of pages13
JournalIEEE Transactions on Audio, Speech and Language Processing
Volume18
Issue number3
DOIs
Publication statusPublished - 1 Mar 2010
Externally publishedYes

Keywords

  • Audio coding
  • Audio indexing
  • Sparse representations
  • Timefrequency representations

Fingerprint

Dive into the research topics of 'Audio signal representations for indexing in the transform domain'. Together they form a unique fingerprint.

Cite this