Odyssey 2014

We address the problem of named speaker identification in TV broadcast which consists in answering the question “who speaks when?” with the real identity of speakers, using person names automatically obtained from speech transcripts. While existing approaches rely on a first speaker diarization step followed by a local name propagation step to speaker clusters, we propose a unified framework called person instance graph where both steps are jointly modeled as a global optimization problem, then solved using integer linear programming. Moreover, when available, acoustic speaker models can be added seamlessly to the graph structure for joint named and acoustic speaker identification – leading to a 10% error decrease (from 45% down to 35%) over a state-of-the-art i-vector speaker identification system on the REPERE TV broadcast corpus.