Multimodal Indexing of Multilingual News Video
The problems associated with automatic analysis of news telecasts are more severe in a country like India, where there are many national and regional language channels, besides English. In this paper, we present a framework for multimodal analysis of multilingual news telecasts, which can be augmen...
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doaj-f14ffcb084124ec69bf3433087f619d82020-11-24T21:29:57ZengHindawi LimitedInternational Journal of Digital Multimedia Broadcasting1687-75781687-75862010-01-01201010.1155/2010/486487486487Multimodal Indexing of Multilingual News VideoHiranmay Ghosh0Sunil Kumar Kopparapu1Tanushyam Chattopadhyay2Ashish Khare3Sujal Subhash Wattamwar4Amarendra Gorai5Meghna Pandharipande6TCS Innovation Labs Delhi, TCS Towers, 249 D&E Udyog Vihar Phase IV, Gurgaon 122015, IndiaTCS Innovation Labs Mumbai, Yantra Park, Pokhran Road no. 2, Thane West 400601, IndiaTCS Innovation Labs Kolkata, Plot A2, M2-N2 Sector 5, Block GP, Salt Lake Electronics Complex, Kolkata 700091, IndiaTCS Innovation Labs Delhi, TCS Towers, 249 D&E Udyog Vihar Phase IV, Gurgaon 122015, IndiaTCS Innovation Labs Delhi, TCS Towers, 249 D&E Udyog Vihar Phase IV, Gurgaon 122015, IndiaTCS Innovation Labs Delhi, TCS Towers, 249 D&E Udyog Vihar Phase IV, Gurgaon 122015, IndiaTCS Innovation Labs Mumbai, Yantra Park, Pokhran Road no. 2, Thane West 400601, IndiaThe problems associated with automatic analysis of news telecasts are more severe in a country like India, where there are many national and regional language channels, besides English. In this paper, we present a framework for multimodal analysis of multilingual news telecasts, which can be augmented with tools and techniques for specific news analytics tasks. Further, we focus on a set of techniques for automatic indexing of the news stories based on keywords spotted in speech as well as on the visuals of contemporary and domain interest. English keywords are derived from RSS feed and converted to Indian language equivalents for detection in speech and on ticker texts. Restricting the keyword list to a manageable number results in drastic improvement in indexing performance. We present illustrative examples and detailed experimental results to substantiate our claim.http://dx.doi.org/10.1155/2010/486487 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hiranmay Ghosh Sunil Kumar Kopparapu Tanushyam Chattopadhyay Ashish Khare Sujal Subhash Wattamwar Amarendra Gorai Meghna Pandharipande |
spellingShingle |
Hiranmay Ghosh Sunil Kumar Kopparapu Tanushyam Chattopadhyay Ashish Khare Sujal Subhash Wattamwar Amarendra Gorai Meghna Pandharipande Multimodal Indexing of Multilingual News Video International Journal of Digital Multimedia Broadcasting |
author_facet |
Hiranmay Ghosh Sunil Kumar Kopparapu Tanushyam Chattopadhyay Ashish Khare Sujal Subhash Wattamwar Amarendra Gorai Meghna Pandharipande |
author_sort |
Hiranmay Ghosh |
title |
Multimodal Indexing of Multilingual News Video |
title_short |
Multimodal Indexing of Multilingual News Video |
title_full |
Multimodal Indexing of Multilingual News Video |
title_fullStr |
Multimodal Indexing of Multilingual News Video |
title_full_unstemmed |
Multimodal Indexing of Multilingual News Video |
title_sort |
multimodal indexing of multilingual news video |
publisher |
Hindawi Limited |
series |
International Journal of Digital Multimedia Broadcasting |
issn |
1687-7578 1687-7586 |
publishDate |
2010-01-01 |
description |
The problems associated with automatic analysis of news telecasts are more severe in a country like India, where there are many national and regional language channels, besides English. In this paper, we present a framework for multimodal analysis of multilingual news telecasts, which can be augmented with tools and techniques for specific news analytics tasks. Further, we focus on a set of techniques for automatic indexing of the news stories based on keywords spotted in speech as well as on the visuals of contemporary and domain interest. English keywords are derived from RSS feed and converted to Indian language equivalents for detection in speech and on ticker texts. Restricting the keyword list to a manageable number results in drastic improvement in indexing performance. We present illustrative examples and detailed experimental results to substantiate our claim. |
url |
http://dx.doi.org/10.1155/2010/486487 |
work_keys_str_mv |
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