Unsupervised naming of speakers in broadcast TV: using written names, pronounced names or both?

Persons identification in video from TV broadcast is a valuable tool for indexing them. However, the use of biometric models is not a very sustainable option without a priori knowledge of people present in the videos. The pronounced names (PN) or written names (WN) on the screen can provide hypotheses names for speakers. We propose an experimental comparison of the potential of these two modalities (names pronounced or written) to extract the true names of the speakers. The names pronounced offer many instances of citation but transcription and named-entity detection errors halved the potential of this modality. On the contrary, the written names detection benefits of the video quality improvement and is nowadays rather robust and efficient to name speakers. Oracle experiments presented for the mapping between written names and speakers also show the complementarity of both PN and WN modalities. Index Terms: Speaker identification, OCR, ASR

[1]  Jean-Luc Gauvain,et al.  Partitioning and transcription of broadcast news data , 1998, ICSLP.

[2]  Sue Tranter.  Who Really Spoke When? Finding Speaker Turns and Identities in Broadcast News Audio , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[3]  Olivier Galibert,et al.  The REPERE Corpus : a multimodal corpus for person recognition , 2012, LREC.

[4]  Jean-Luc Gauvain,et al.  The LIMSI Broadcast News transcription system , 2002, Speech Commun..

[5]  Jean-Luc Gauvain,et al.  Speaker diarization from speech transcripts , 2004, INTERSPEECH.

[6]  François Yvon,et al.  Practical Very Large Scale CRFs , 2010, ACL.

[7]  Olivier Galibert,et al.  LIMSI participation in the QAst 2009 track , 2009, CLEF.

[8]  Sophie Rosset,et al.  Models Cascade for Tree-Structured Named Entity Detection , 2011, IJCNLP.

[9]  Georges Quénot,et al.  Unsupervised Speaker Identification using Overlaid Texts in TV Broadcast , 2012, INTERSPEECH.

[10]  Alexandre Allauzen,et al.  Training and Evaluation of POS Taggers on the French MULTITAG Corpus , 2008, LREC.

[11]  Georges Quénot,et al.  From Text Detection in Videos to Person Identification , 2012, 2012 IEEE International Conference on Multimedia and Expo.

[12]  L. Lamel,et al.  A comparative study using manual and automatic transcriptions for diarization , 2005, IEEE Workshop on Automatic Speech Recognition and Understanding, 2005..

[13]  Ngoc Thang Vu,et al.  Speech recognition for machine translation in Quaero , 2011, IWSLT.

[14]  Julie Mauclair,et al.  Speaker Diarization: About whom the Speaker is Talking ? , 2006, 2006 IEEE Odyssey - The Speaker and Language Recognition Workshop.

[15]  Paul Deléglise,et al.  Extracting true speaker identities from transcriptions , 2007, INTERSPEECH.

[16]  Sylvain Meignier,et al.  Automatic named identification of speakers using diarization and ASR systems , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.