
Abstract
The fact that an increasing number of functions in the automobile are and will be controlled by speech of the driver rises the question whether this speech input may be used to detect a possible alcoholic intoxication of the driver. For that matter a large part of the new Alcohol Language Corpus (ALC) edited by the Bavarian Archive of Speech Signals (BAS) will be used for a broad statistical investigation of possible feature candidates for classification. In this contribution we present the motivation and the design of the ALC corpus as well as first results from fundamental frequency and rhythm analysis. Our analysis by comparing sober and alcoholized speech of the same individuals suggests that there are in fact promising features that can automatically be derived from the speech signal during the speech recognition process and will indicate intoxication for most speakers.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | alcohol detection, speaker characteristics, speech corpus, Alcohol Language Corpus, BAS |
Faculties: | Languages and Literatures > Department 2 > Speech Science |
Subjects: | 400 Language > 400 Language |
URN: | urn:nbn:de:bvb:19-epub-13683-2 |
Language: | English |
Item ID: | 13683 |
Date Deposited: | 19. Jul 2012 11:48 |
Last Modified: | 04. Nov 2020 12:54 |