Language Independent Search in MediaEval's Spoken Web Search Task

Abstract

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