Towards Awareness of Human Relational Strategies in Virtual Agents
| Autor: | Abdullah Mueen, Ian Beaver, Cynthia Freeman |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Service (systems architecture)
Computer science media_common.quotation_subject 05 social sciences 020207 software engineering 02 engineering and technology General Medicine Personality psychology 050105 experimental psychology Task (project management) Annotation Order (business) Human–computer interaction Gratitude 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences Baseline (configuration management) media_common |
| Zdroj: | AAAI |
| ISSN: | 2374-3468 2159-5399 |
| DOI: | 10.1609/aaai.v34i03.5644 |
| Popis: | As Intelligent Virtual Agents (IVAs) increase in adoption and further emulate human personalities, we are interested in how humans apply relational strategies to them compared to other humans in a service environment. Human-computer data from three live customer service IVAs was collected, and annotators marked all text that was deemed unnecessary to the determination of user intention as well as the presence of multiple intents. After merging the selections of multiple annotators, a second round of annotation determined the classes of relational language present in the unnecessary sections such as Greetings, Backstory, Justification, Gratitude, Rants, or Expressing Emotions. We compare the usage of such language in human-human service interactions. We show that removal of this language from task-based inputs has a positive effect by both an increase in confidence and improvement in responses, as evaluated by humans, demonstrating the need for IVAs to anticipate relational language injection. This work provides a methodology to identify relational segments and a baseline of human performance in this task as well as laying the groundwork for IVAs to reciprocate relational strategies in order to improve their believeability. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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