A new conversation corpus in the area of human-computer interaction is introduced. It consists of conversations between one and two interaction partners with a commercial voice assistant system (Amazon’s ALEXA) in two different settings. The fundamental aim for building up this corpus is to investigate how humans address technical systems. Thereby, two different scenarios, a formal and an informal one, are designed. The scenarios are conducted by the participants alone and with an accompanying person. Furthermore, questionnaires are used to get a self-evaluation of the participants in terms of their experience of the interaction and their conscious changes in voice and behaviour while addressing a technical system. Additionally, also their experience with technical systems and the evaluation of the utilized commercial voice assistant is retrieved via questionnaires. The corpus consists of high-quality microphone recordings of 27 German speaking subjects, all students at the University Magdeburg.
@InProceedings{SIEGERT18.13, author = {Ingo Siegert ,Julia Krüger ,Olga Egorow ,Jannik Nietzold ,Ralph Heinemann and Alicia Lotz}, title = {Voice Assistant Conversation Corpus (VACC): A Multi-Scenario Dataset for Addressee Detection in Human-Computer-Interaction using Amazon's ALEXA}, booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {may}, date = {7-12}, location = {Miyazaki, Japan}, editor = {Hanae Koiso and Patrizia Paggio}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-16-0}, language = {english} }
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