A number of paralinguistic problems are often dealt with in isolation, such as emotion, health state or personality. However, there are also good examples of mutual benefit, mostly incorporating speaker gender knowledge. In this paper we deal with the question how further paralinguistic information, such as speaker age, height, or race can provide beneficial information when their ground truth knowledge is provided within single-task speaker classification. Tests with openSMILE's 1.5 k Paralinguistic Challenge Feature set on the TIMIT corpus of 630 speakers reveal significant boost in accuracy or cross-correlation|depending on the representation form of the problem at hand.
Authors:
Schuller, Björn; Wöllmer, Martin; Eyben, Florian; Rigoll, Gerhard; Arsic, Dejan
Affiliations:
Müller-BBM Vibroakustiksysteme, Planegg, Germany; Technische Universität München, Munich, Germany(See document for exact affiliation information.)
AES Conference:
42nd International Conference: Semantic Audio (July 2011)
Paper Number:
2-1
Publication Date:
July 22, 2011
Subject:
Speech Processing and Analysis
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.