@inproceedings{schiel-etal-2008-alc,
title = "{ALC}: Alcohol Language Corpus",
author = {Schiel, Florian and
Heinrich, Christian and
Barf\"u\ss er, Sabine and
Gilg, Thomas},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L08-1502/",
abstract = "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."
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T ALC: Alcohol Language Corpus
%A Schiel, Florian
%A Heinrich, Christian
%A Barfüß er, Sabine
%A Gilg, Thomas
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F schiel-etal-2008-alc
%X 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.
%U https://aclanthology.org/L08-1502/
Markdown (Informal)
[ALC: Alcohol Language Corpus](https://aclanthology.org/L08-1502/) (Schiel et al., LREC 2008)
ACL
- Florian Schiel, Christian Heinrich, Sabine Barfüßer, and Thomas Gilg. 2008. ALC: Alcohol Language Corpus. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).