Challenges of Applying Automatic Speech Recognition for Transcribing EUParliament Committee Meetings: A Pilot StudyHugo de Vos and Suzan VerberneInstitute of Public Administration and Leiden Institute of Advanced Computer Science, Leiden Universityh.firstname.lastname@example.org, email@example.comAbstractWe tested the feasibility of automatically transcribing committee meetings of the European Union parliament with the use of AutomaticSpeech Recognition techniques. These committee meetings contain more valuable information for political science scholars than theplenary meetings since these meetings showcase actual debates opposed to the more formal plenary meetings. However, since there areno transcriptions of those meetings, they are a lot less accessible for research than the plenary meetings, of which multiple corpora exist. We explored a freely available ASR application and analysed the output in order to identify the weaknesses of an out-of-the box system. We followed up on those weaknesses by proposing directions for optimizing the ASR for our goals. We found that, despite showcasingacceptable results in terms of Word Error Rate, the model did not yet suffice for the purpose of generating a data set for use in PoliticalScience. The application was unable to successfully recognize domain specific terms and names. To overcome this issue, future researchwill be directed at using domain specific language models in combination with off-the-shelf acoustic models.