Abstract
We introduce a novel approach for automatically generating a virtual instructor from textual input only. Our fully implemented system first analyzes the rhetorical structure of the input text and then creates various question-answer pairs using patterns. These patterns have been derived from correlations found between rhetorical structure of monologue texts and question-answer pairs in the corresponding dialogues. A selection of the candidate pairs is verbalized into a diverse collection of question-answer pairs. Finally the system compiles the collection of question-answer pairs into scripts for a virtual instructor. Our end-to-end system presents questions in pre-fixed order and the agent answers them. Our system was evaluated with a group of twenty-four subjects. The evaluation was conducted using three informed consent documents of clinical trials from the domain of colon cancer. Each of the documents was explained by a virtual instructor using 1) text, 2) text and agent monologue, and 3) text and agent performing question-answering. Results show that an agent explaining an informed consent document did not provide significantly better comprehension scores, but did score higher on satisfaction, compared to two control conditions.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 1-14 |
| Number of pages | 14 |
| Volume | 7502 LNAI |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | 12th International Conference on Intelligent Virtual Agents, IVA 2012 - Santa Cruz, CA Duration: 2012 Sep 12 → 2012 Sep 14 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 7502 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 12th International Conference on Intelligent Virtual Agents, IVA 2012 |
|---|---|
| City | Santa Cruz, CA |
| Period | 12/9/12 → 12/9/14 |
Fingerprint
Keywords
- Dialogue Generation
- Medical Documents
- Rhetorical Structure Theory
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Fully automated generation of question-answer pairs for scripted virtual instruction. / Kuyten, Pascal; Bickmore, Timothy; Stoyanchev, Svetlana; Piwek, Paul; Prendinger, Helmut; Ishizuka, Mitsuru.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7502 LNAI 2012. p. 1-14 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7502 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Fully automated generation of question-answer pairs for scripted virtual instruction
AU - Kuyten, Pascal
AU - Bickmore, Timothy
AU - Stoyanchev, Svetlana
AU - Piwek, Paul
AU - Prendinger, Helmut
AU - Ishizuka, Mitsuru
PY - 2012
Y1 - 2012
N2 - We introduce a novel approach for automatically generating a virtual instructor from textual input only. Our fully implemented system first analyzes the rhetorical structure of the input text and then creates various question-answer pairs using patterns. These patterns have been derived from correlations found between rhetorical structure of monologue texts and question-answer pairs in the corresponding dialogues. A selection of the candidate pairs is verbalized into a diverse collection of question-answer pairs. Finally the system compiles the collection of question-answer pairs into scripts for a virtual instructor. Our end-to-end system presents questions in pre-fixed order and the agent answers them. Our system was evaluated with a group of twenty-four subjects. The evaluation was conducted using three informed consent documents of clinical trials from the domain of colon cancer. Each of the documents was explained by a virtual instructor using 1) text, 2) text and agent monologue, and 3) text and agent performing question-answering. Results show that an agent explaining an informed consent document did not provide significantly better comprehension scores, but did score higher on satisfaction, compared to two control conditions.
AB - We introduce a novel approach for automatically generating a virtual instructor from textual input only. Our fully implemented system first analyzes the rhetorical structure of the input text and then creates various question-answer pairs using patterns. These patterns have been derived from correlations found between rhetorical structure of monologue texts and question-answer pairs in the corresponding dialogues. A selection of the candidate pairs is verbalized into a diverse collection of question-answer pairs. Finally the system compiles the collection of question-answer pairs into scripts for a virtual instructor. Our end-to-end system presents questions in pre-fixed order and the agent answers them. Our system was evaluated with a group of twenty-four subjects. The evaluation was conducted using three informed consent documents of clinical trials from the domain of colon cancer. Each of the documents was explained by a virtual instructor using 1) text, 2) text and agent monologue, and 3) text and agent performing question-answering. Results show that an agent explaining an informed consent document did not provide significantly better comprehension scores, but did score higher on satisfaction, compared to two control conditions.
KW - Dialogue Generation
KW - Medical Documents
KW - Rhetorical Structure Theory
UR - http://www.scopus.com/inward/record.url?scp=84867519134&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867519134&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33197-8-1
DO - 10.1007/978-3-642-33197-8-1
M3 - Conference contribution
AN - SCOPUS:84867519134
SN - 9783642331961
VL - 7502 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 14
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -