On the Use of Linguistic Information for Broadcast News Speaker Tracking

In this paper, we have explored a speaker characterization at two different linguistic levels, the lexical content and the syntactical form, in the context of broadcast news (BN) speaker tracking task. The modeling of the information is done classically, by a n-gram approach applied on the word sequence for the linguistic content and on the syntactical tags issued from this sequence for the syntactical level (n-class modeling). The experiments were done on a subset of the BN rich transcription French evaluation campaign, ESTER. We have observed that lexical information is not useful for BN data while the syntactical information seems promising as it allows significant speaker identification and verification performance (until 40% of correct identification rate and 35% of EER)