Filtering the Unknown: Speech Activity Detection in Heterogeneous Video Collections

Abstract

In this paper we discuss the speech activity detection system that we used for detecting speech regions in the Dutch TRECVID video collection. The system is designed to filter non-speech like music or sound effects out of the signal without the use of predefined non-speech models. Because the system trains its models on-line, it is robust for handling out-of-domain data. The speech activity error rate on an out-of-domain test set, recordings of English conference meetings, was 4.4%. The overall error rate on twelve randomly selected five minute TRECVID fragments was 11.5%