Towards Automatic Identification of Effective Clues for Team Word-Guessing Games

Eli Pincus, David Traum


Abstract
Team word-guessing games where one player, the clue-giver, gives clues attempting to elicit a target-word from another player, the receiver, are a popular form of entertainment and also used for educational purposes. Creating an engaging computational agent capable of emulating a talented human clue-giver in a timed word-guessing game depends on the ability to provide effective clues (clues able to elicit a correct guess from a human receiver). There are many available web resources and databases that can be mined for the raw material for clues for target-words; however, a large number of those clues are unlikely to be able to elicit a correct guess from a human guesser. In this paper, we propose a method for automatically filtering a clue corpus for effective clues for an arbitrary target-word from a larger set of potential clues, using machine learning on a set of features of the clues, including point-wise mutual information between a clue’s constituent words and a clue’s target-word. The results of the experiments significantly improve the average clue quality over previous approaches, and bring quality rates in-line with measures of human clue quality derived from a corpus of human-human interactions. The paper also introduces the data used to develop this method; audio recordings of people making guesses after having heard the clues being spoken by a synthesized voice.
Anthology ID:
L16-1435
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2741–2747
Language:
URL:
https://aclanthology.org/L16-1435
DOI:
Bibkey:
Cite (ACL):
Eli Pincus and David Traum. 2016. Towards Automatic Identification of Effective Clues for Team Word-Guessing Games. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2741–2747, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Towards Automatic Identification of Effective Clues for Team Word-Guessing Games (Pincus & Traum, LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1435.pdf