NIST RT’05S Evaluation: Pre-processing Techniques and Speaker Diarization on Multiple Microphone Meetings

  • Dan Istrate
  • Corinne Fredouille
  • Sylvain Meignier
  • Laurent Besacier
  • Jean François Bonastre
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3869)


This paper presents different pre-processing techniques, coupled with three speaker diarization systems in the framework of the NIST 2005 Spring Rich Transcription campaign (RT’05S).

The pre-processing techniques aim at providing a signal quality index in order to build a unique “virtual” signal obtained from all the microphone recordings available for a meeting. This unique virtual signal relies on a weighted sum of the different microphone signals while the signal quality index is given according to a signal to noise ratio.

Two methods are used in this paper to compute the instantaneous signal to noise ratio: a speech activity detection based approach and a noise spectrum estimate. The speaker diarization task is performed using systems developed by different labs: the LIA, LIUM and CLIPS. Among the different system submissions made by these three labs, the best system obtained 24.5 % speaker diarization error for the conference subdomain and 18.4 % for the lecture subdomain.


Broadcast News Evaluation Campaign Speaker Model Meeting Data Cepstral Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dan Istrate
    • 1
  • Corinne Fredouille
    • 1
  • Sylvain Meignier
    • 2
  • Laurent Besacier
    • 3
  • Jean François Bonastre
    • 1
  1. 1.LIA-AvignonAvignonFrance
  2. 2.LIUMLe MansFrance
  3. 3.CLIPS-IMAG (UJF & CNRS & INPG)GrenobleFrance

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