A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design
Abstract
Audio fingerprinting, also named as audio hashing, has been well-known as a powerful technique to perform audio identification and synchronization. It basically involves two major steps: fingerprint (voice pattern) design and matching search. While the first step concerns the derivation of a robust and compact audio signature, the second step usually requires knowledge about database and quick-search algorithms. Though this technique offers a wide range of real-world applications, to the best of the authors' knowledge, a comprehensive survey of existing algorithms appeared more than eight years ago. Thus, in this paper, we present a more up-to-date review and, for emphasizing on the audio signal processing aspect, we focus our state-of-the-art survey on the fingerprint design step for which various audio features and their tractable statistical models are discussed.
Cite
@article{arxiv.1502.06811,
title = {A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design},
author = {Ngoc Q. K. Duong and Hien-Thanh Duong},
journal= {arXiv preprint arXiv:1502.06811},
year = {2015}
}
Comments
http://www.iaria.org/conferences2015/PATTERNS15.html ; Seventh International Conferences on Pervasive Patterns and Applications (PATTERNS 2015), Mar 2015, Nice, France