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
