The retrieval of sounds in large databases can benefit from novel paradigms that exploit human-computer interaction. This work introduces the use of non-speech voice imitations as input queries in a large user-contributed sound repository. We address first the analysis of the human voice properties when imitating sounds. Second, we study the automatic classification of voice imitations in clusters by means of user experiments. Finally, we present an evaluation that demonstrates the potential of a content-based classification using voice imitations as input queries. Future perspectives for using voice interfaces in sound assets retrieval are exposed.

Authors: Blancas, David Sanchez; Janer, Jordi
Affiliation: Pompeu Fabra University, Barcelona, Spain
AES Conference: 53rd International Conference: Semantic Audio (January 2014)
Paper Number: P2-8
Publication Date: January 27, 2014 Import into BibTeX
Subject: Content-Based Audio Retrieval
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=17094

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location: (CD 53rdPapers)   /conf/53/aes53-000040.pdf

Start a discussion about this paper!