ITEM METADATA RECORD
Title: The self-taught vocal interface
Authors: Ons, Bart ×
Gemmeke, Jort
Van hamme, Hugo #
Issue Date: 19-Dec-2014
Publisher: Hindawi Publishing Corp.
Series Title: EURASIP Journal on Audio, Speech and Music Processing vol:43 pages:1-16
Abstract: Speech technology is firmly rooted in daily life, most notably in command-and-control (C&C) applications. C&C usability downgrades quickly, however, when used by people with non-standard speech. We pursue a fully adaptive vocal user interface (VUI) which can learn both vocabulary and grammar directly from interaction examples, achieving robustness against non-standard speech by building up models from scratch. This approach raises feasibility concerns on the amount of training material required to yield an acceptable recognition accuracy. In a previous work, we proposed a VUI based on non-negative matrix factorisation (NMF) to find recurrent acoustic and semantic patterns comprising spoken commands and device-specific actions, and showed its effectiveness on unimpaired speech. In this work, we evaluate the feasibility of a self-taught VUI on a new database called DOMOTICA-3, which contains dysarthric speech with typical commands in a home automation setting. Additionally, we compare our NMF-based system with a system based on Gaussian mixtures. The evaluation favours our NMF-based approach, yielding feasible recognition accuracies for people with dysarthric speech after a few learning examples. Finally, we propose the use of a multi-layered semantic frame structure and demonstrate its effectiveness in boosting overall performance.
Description: Ons B., Gemmeke J.F., Van hamme H., ''The self-taught vocal interface'', EURASIP journal on audio, speech, and music processing, vol. 43, 16 pp., 2014.
URI: 
ISSN: 1687-4722
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - PSI, Processing Speech and Images
× corresponding author
# (joint) last author

Files in This Item:
File Description Status SizeFormat
3837_final_OA.pdfOA article Published 1228KbAdobe PDFView/Open

 


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science