@inproceedings{22a8a7f74e3047119220470806470de9,
title = "Simulating zero-resource spoken term discovery",
abstract = "If search engines are ever to index all of the spoken content in the world, they will need to handle hundreds of languages for which no automatic speech recognition systems exist. Zero-resource spoken term discovery, in which repeated content is detected in some acoustic representation, offers a potentially useful source of indexing features. This paper describes a text-based simulation of a zero-resource spoken term discovery system that allows any information retrieval test collection to be used as a basis for early development of information retrieval techniques. It is proposed that these techniques can be later applied to actual zero-resource spoken term discovery results.",
keywords = "N-gram retrieval, Simulation, Zero resource term discovery",
author = "Jerome White and Oard, {Douglas W.}",
note = "Publisher Copyright: {\textcopyright} 2017 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery.; 26th ACM International Conference on Information and Knowledge Management, CIKM 2017 ; Conference date: 06-11-2017 Through 10-11-2017",
year = "2017",
month = nov,
day = "6",
doi = "10.1145/3132847.3133160",
language = "English (US)",
series = "International Conference on Information and Knowledge Management, Proceedings",
publisher = "Association for Computing Machinery",
pages = "2371--2374",
booktitle = "CIKM 2017 - Proceedings of the 2017 ACM Conference on Information and Knowledge Management",
}