Paper: Morphological Segmentation for Keyword Spotting

ACL ID D14-1095
Title Morphological Segmentation for Keyword Spotting
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

We explore the impact of morpholog- ical segmentation on keyword spotting (KWS). Despite potential benefits, state- of-the-art KWS systems do not use mor- phological information. In this paper, we augment a state-of-the-art KWS sys- tem with sub-word units derived from su- pervised and unsupervised morphological segmentations, and compare with phonetic and syllabic segmentations. Our exper- iments demonstrate that morphemes im- prove overall performance of KWS sys- tems. Syllabic units, however, rival the performance of morphological units when used in KWS. By combining morphologi- cal, phonetic and syllabic segmentations, we demonstrate substantial performance gains.