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A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design

Ngoc Q. K. Duong 1, * Hien-Thanh Duong 2 
* Corresponding author
1 Technicolor Imaging Science Lab
Technicolor [Cesson Sévigné]
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.
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Submitted on : Tuesday, February 24, 2015 - 2:43:36 PM
Last modification on : Thursday, August 29, 2019 - 4:50:07 PM
Long-term archiving on: : Wednesday, May 27, 2015 - 9:52:37 AM


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  • HAL Id : hal-01119503, version 1
  • ARXIV : 1502.06811


Ngoc Q. K. Duong, Hien-Thanh Duong. A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design. Seventh International Conferences on Pervasive Patterns and Applications (PATTERNS 2015), Mar 2015, Nice, France. ⟨hal-01119503⟩



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