Language independent search in MediaEval's Spoken Web Search task

被引:31
|
作者
Metze, Florian [1 ]
Anguera, Xavier [3 ]
Barnard, Etienne [2 ]
Davel, Marelie [2 ]
Gravier, Guillaume [4 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[2] North West Univ, Vanderbijlpark, South Africa
[3] Telefon Res, Barcelona, Spain
[4] CNRS IRISA, Rennes, France
来源
COMPUTER SPEECH AND LANGUAGE | 2014年 / 28卷 / 05期
关键词
Low-resource speech technology; Evaluation; Spoken web; Spoken term detection;
D O I
10.1016/j.csl.2013.12.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we describe several approaches to language-independent spoken term detection and compare their performance on a common task, namely "Spoken Web Search". The goal of this part of the MediaEval initiative is to perform low-resource language-independent audio search using audio as input. The data was taken from "spoken web" material collected over mobile phone connections by IBM India as well as from the LWAZI corpus of African languages. As part of the 2011 and 2012 MediaEval benchmark campaigns, a number of diverse systems were implemented by independent teams, and submitted to the "Spoken Web Search" task. This paper presents the 2011 and 2012 results, and compares the relative merits and weaknesses of approaches developed by participants, providing analysis and directions for future research, in order to improve voice access to spoken information in low resource settings. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1066 / 1082
页数:17
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