Paper Info
Title
A stream-based audio segmentation, classification and clustering pre-processing system for broadcast news using ANN models
Abstract
Abstract This paper describes our work on the development,of a low la- tency stream-based audio pre-processing system for broadcast news using model-based techniques. It performs,speech/non- speech classification, speaker segmentation, speaker clustering, gender and background,conditions classification. As a way to increase the modelling,accuracy our algorithms make,exten- sive use of Artificial Neural Networks (ANN) thus avoiding the rough assumptions,normally made,about the audio signal dis- tribution. Experiments were conducted on the COST278 multi- lingual TV broadcast news database and compared,with current state of the art algorithms using standard evaluation tools. Ad- ditionally we investigated the impact of automatic audio pre- processing system within the recognition using a large broad- cast news,test database for the European Portuguese. These testsshow a smalldegradation,in recognition performance,when compared,with hand labelled audio segmentation. Our system is part of a prototype close-captioning system that is daily pro- cessing the main news show of two Portuguese Broadcasters.
Year
Venue
Keywords
2005
INTERSPEECH
artificial neural network
DocType
Citations 
PageRank 
Conference
16
1.26
References 
Authors
5
2
Name
Order
Citations
PageRank
Hugo Meinedo125725.35
João Paulo Neto229132.69