Thomas Kisler


MOCCA: Measure of Confidence for Corpus Analysis - Automatic Reliability Check of Transcript and Automatic Segmentation
Thomas Kisler | Florian Schiel
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


The BAS Speech Data Repository
Uwe Reichel | Florian Schiel | Thomas Kisler | Christoph Draxler | Nina Pörner
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The BAS CLARIN speech data repository is introduced. At the current state it comprises 31 pre-dominantly German corpora of spoken language. It is compliant to the CLARIN-D as well as the OLAC requirements. This enables its embedding into several infrastructures. We give an overview over its structure, its implementation as well as the corpora it contains.

BAS Speech Science Web Services - an Update of Current Developments
Thomas Kisler | Uwe Reichel | Florian Schiel | Christoph Draxler | Bernhard Jackl | Nina Pörner
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In 2012 the Bavarian Archive for Speech Signals started providing some of its tools from the field of spoken language in the form of Software as a Service (SaaS). This means users access the processing functionality over a web browser and therefore do not have to install complex software packages on a local computer. Amongst others, these tools include segmentation & labeling, grapheme-to-phoneme conversion, text alignment, syllabification and metadata generation, where all but the last are available for a variety of languages. Since its creation the number of available services and the web interface have changed considerably. We give an overview and a detailed description of the system architecture, the available web services and their functionality. Furthermore, we show how the number of files processed over the system developed in the last four years.


German Alcohol Language Corpus - the Question of Dialect
Florian Schiel | Thomas Kisler
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Speech uttered under the influence of alcohol is known to deviate from the speech of the same person when sober. This is an important feature in forensic investigations and could also be used to detect intoxication in the automotive environment. Aside from acoustic-phonetic features and speech content which have already been studied by others in this contribution we address the question whether speakers use dialectal variation or dialect words more frequently when intoxicated than when sober. We analyzed 300,000 recorded word tokens in read and spontaneous speech uttered by 162 female and male speakers within the German Alcohol Language Corpus. We found that contrary to our expectations the frequency of dialectal forms decreases significantly when speakers are under the influence. We explain this effect with a compensatory over-shoot mechanism: speakers are aware of their intoxication and that they are being monitored. In forensic analysis of speech this `awareness factor’ must be taken into account.