Induced Inflection-Set Keyword Search in Speech

Oliver Adams, Matthew Wiesner, Jan Trmal, Garrett Nicolai, David Yarowsky


Abstract
We investigate the problem of searching for a lexeme-set in speech by searching for its inflectional variants. Experimental results indicate how lexeme-set search performance changes with the number of hypothesized inflections, while ablation experiments highlight the relative importance of different components in the lexeme-set search pipeline and the value of using curated inflectional paradigms. We provide a recipe and evaluation set for the community to use as an extrinsic measure of the performance of inflection generation approaches.
Anthology ID:
2020.sigmorphon-1.25
Volume:
Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
July
Year:
2020
Address:
Online
Editors:
Garrett Nicolai, Kyle Gorman, Ryan Cotterell
Venue:
SIGMORPHON
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
210–216
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2020.sigmorphon-1.25/
DOI:
10.18653/v1/2020.sigmorphon-1.25
Bibkey:
Cite (ACL):
Oliver Adams, Matthew Wiesner, Jan Trmal, Garrett Nicolai, and David Yarowsky. 2020. Induced Inflection-Set Keyword Search in Speech. In Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 210–216, Online. Association for Computational Linguistics.
Cite (Informal):
Induced Inflection-Set Keyword Search in Speech (Adams et al., SIGMORPHON 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2020.sigmorphon-1.25.pdf
Video:
 http://slideslive.com/38929878
Code
 oadams/inflection-kws