Language independent search in MediaEval's Spoken Web Search task

In this paper, we describe several approaches to language-independent spoken term detection and compare their performance n a common task, namely “Spoken Web Search”. The goal of this part of the MediaEval initiative is to perform low-resource anguage-independent audio search using audio as input. The data was taken from “spoken web” material collected over mobile hone connections by IBM India as well as from the LWAZI corpus of African languages. As part of the 2011 and 2012 MediaEval enchmark campaigns, a number of diverse systems were implemented by independent teams, and submitted to the “Spoken Web earch” task. This paper presents the 2011 and 2012 results, and compares the relative merits and weaknesses of approaches developed y participants, providing analysis and directions for future research, in order to improve voice access to spoken information in low esource settings. 2014 Elsevier Ltd. All rights reserved.