dc.contributor.author | van Heerden, Charl | |
dc.contributor.author | Karakos, Damianos | |
dc.contributor.author | Narasimhan, Karthik | |
dc.contributor.author | Schwartz, Richard | |
dc.contributor.author | Davel, Marelie H. | |
dc.date.accessioned | 2018-02-27T10:06:59Z | |
dc.date.available | 2018-02-27T10:06:59Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Charl van Heerden, Damianos Karakos, Karthik Narasimhan, Marelie Davel and Richard Schwartz, “Constructing sub-word units for spoken term detection”, in Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp 5780-5784, New Orleans, Louisiana, 2017. [http://engineering.nwu.ac.za/multilingual-speech-technologies-must/publications] | |
dc.identifier.uri | http://hdl.handle.net/10394/26442 | |
dc.identifier.uri | https://pdfs.semanticscholar.org/f28e/39372d12d1279ea775a80df3e63f86069706.pdf | |
dc.description.abstract | Spoken term detection, especially of out-of-vocabulary (OOV) keywords,
benefits from the use of sub-word systems. We experiment
with different language-independent approaches to sub-word unit
generation, generating both syllable-like and morpheme-like units,
and demonstrate how the performance of syllable-like units can be
improved by artificially increasing the number of unique units. The
effect of unit choice is empirically evaluated using the eight languages
from the 2016 IARPA BABEL evaluation.
Index Terms— Spoken term detection, BABEL, sub-words,
syllables, morphemes. | en_US |
dc.description.sponsorship | We would like to thank all members of the Babelon team at Raytheon
BBN Technologies, and especially Tanel Alumae, William Hartmann
and Stavros Tsakalidis. This work was supported by the Intelligence
Advanced Research Projects Activity (IARPA) via Department
of Defense U.S. Army Research Laboratory contract number
W911NF-12-C-0013. The U.S. Government is authorized to reproduce
and distribute reprints for Governmental purposes notwithstanding
any copyright annotation thereon. Disclaimer: The views
and conclusions contained herein are those of the authors and should
not be interpreted as necessarily representing the official policies or
endorsements, either expressed or implied, of IARPA, DoD/ARL, or
the U.S. Government. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Acoustics, Speech and Signal Processing (ICASSP) | en_US |
dc.subject | Spoken term detection, | en_US |
dc.subject | Effect of unit choice | en_US |
dc.subject | BABEL | en_US |
dc.title | Constructing sub-word units for spoken term detection | en_US |
dc.type | Presentation | en_US |