Speakers enhance contextually confusable words

Eric Meinhardt, Eric Bakovic, Leon Bergen


Abstract
Recent work has found evidence that natural languages are shaped by pressures for efficient communication — e.g. the more contextually predictable a word is, the fewer speech sounds or syllables it has (Piantadosi et al. 2011). Research on the degree to which speech and language are shaped by pressures for effective communication — robustness in the face of noise and uncertainty — has been more equivocal. We develop a measure of contextual confusability during word recognition based on psychoacoustic data. Applying this measure to naturalistic speech corpora, we find evidence suggesting that speakers alter their productions to make contextually more confusable words easier to understand.
Anthology ID:
2020.acl-main.180
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1991–2002
Language:
URL:
https://aclanthology.org/2020.acl-main.180
DOI:
10.18653/v1/2020.acl-main.180
Bibkey:
Cite (ACL):
Eric Meinhardt, Eric Bakovic, and Leon Bergen. 2020. Speakers enhance contextually confusable words. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1991–2002, Online. Association for Computational Linguistics.
Cite (Informal):
Speakers enhance contextually confusable words (Meinhardt et al., ACL 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-2/2020.acl-main.180.pdf
Video:
 http://slideslive.com/38929286