Summary of the paper

Title Voice Assistant Conversation Corpus (VACC): A Multi-Scenario Dataset for Addressee Detection in Human-Computer-Interaction using Amazon's ALEXA
Authors Ingo Siegert, Julia Krüger, Olga Egorow, Jannik Nietzold, Ralph Heinemann and Alicia Lotz
Abstract 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.
Topics Speaking-Style, Addressee Detection, Corpus, Multi-User, Speech Assistant, Multi-Scenario
Full paper Voice Assistant Conversation Corpus (VACC): A Multi-Scenario Dataset for Addressee Detection in Human-Computer-Interaction using Amazon's ALEXA
Bibtex @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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