When listening to foreign radio or TV programs we are able to pick up some information from the way people are interacting with each others and easily identify the most dominant speaker or the person who is interviewed. Our work relies on the existence of clues about speaker roles in acoustic and prosodic low-level features extracted from audio files and from speaker segmentations. In this paper we describe an original language-independent method which achieves the recognition of 5 roles (Anchor, Journalist, Other, Punctual Journalist, Punctual Other) with an accuracy of 85% on a 13-hour corpus composed of 46 documents among which can be found different radio shows. A feature selection method is exploited in order to highlight the most relevant features for every speaker role.
Bibliographic reference. Bigot, Benjamin / Pinquier, Julien / Ferrané, Isabelle / André-Obrecht, Régine (2010): "Looking for relevant features for speaker role recognition", In INTERSPEECH-2010, 1057-1060.