Summary of the paper

Title Strategies to Improve a Speaker Diarisation Tool
Authors David Tavarez, Eva Navas, Daniel Erro and Ibon Saratxaga
Abstract This paper describes the different strategies used to improve the results obtained by an off-line speaker diarisation tool with the Albayzin 2010 diarisation database. The errors made by the system have been analyzed and different strategies have been proposed to reduce each kind of error. Very short segments incorrectly labelled and different appearances of one speaker labelled with different identifiers are the most common errors. A post-processing module that refines the segmentation by retraining the GMM models of the speakers involved has been built to cope with these errors. This post-processing module has been tuned with the training dataset and improves the result of the diarisation system by 16.4% in the test dataset.
Topics Person Identification, Tools, systems, applications, Other
Full paper Strategies to Improve a Speaker Diarisation Tool
Bibtex @InProceedings{TAVAREZ12.711,
  author = {David Tavarez and Eva Navas and Daniel Erro and Ibon Saratxaga},
  title = {Strategies to Improve a Speaker Diarisation Tool},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
Powered by ELDA © 2012 ELDA/ELRA