Abstract
This paper describes ongoing work on selective dissemination of broadcast news. Our pipeline system includes several modules: audio preprocessing, speech recognition, and topic segmentation and indexation. The main goal of this work is to study the impact of earlier errors in the last modules. The impact of audio preprocessing errors is quite small on the speech recognition module, but quite significant in terms of topic segmentation. On the other hand, the impact of speech recognition errors on the topic segmentation and indexation modules is almost negligible. The diagnostic of the errors in these modules is a very important step for the improvement of the prototype of a media watch system described in this paper.
Highlights
The goal of this paper is to give a current overview of a prototype system for selective dissemination of broadcast news (BN) in European Portuguese
Besides having evaluated the audio preprocessing (APP) module on the JE corpus, which is very relevant for the following modules, we have evaluated it on a multilingual BN corpus collected within the framework of a European collaborative action (COST 278—Spoken Language Interaction in Telecommunication)
This paper presented our prototype system for selective dissemination of broadcast news, emphasizing the impact of earlier errors of our pipeline system in the last modules
Summary
The goal of this paper is to give a current overview of a prototype system for selective dissemination of broadcast news (BN) in European Portuguese. The development of this system started during the past ALERT European Project, we are continuously trying to improve it, since it integrates several core technologies that are within the most important research areas of our group. The first of these core technologies is audio preprocessing (APP) or speaker diarization which aims at speech/nonspeech classification, speaker segmentation, speaker clustering, and gender, and background conditions classification. The use of a thematic thesaurus for indexation was requested by RTP (Radio Televisao Portuguesa), the Portuguese Public Broadcast Company, and our former partner in the ALERT Project. We will endeavor to compare our results obtained for a European Portuguese corpus with the state of the art for other languages
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