A number of forensic studies published during the last 50 years report that intoxication with alcohol influences speech in a way that is made manifest in certain features of the speech signal. However, most of these studies are based on data that are not publicly available nor of statistically sufficient size. Furthermore, in spite of the positive reports nobody ever successfully implemented a method to detect alcoholic intoxication from the speech signal. The Alcohol Language Corpus (ALC) aims to answer these open questions by providing a publicly available large and statistically sound corpus of intoxicated and sober speech. This paper gives a detailed description of the corpus features and methodology. Also, we will present some preliminary results on a series of verifications about reported potential features that are claimed to reliably indicate alcoholic intoxication.