E-HMM approach for learning and adapting sound models for speaker indexing

@inproceedings{Meignier2001EHMMAF,
  title={E-HMM approach for learning and adapting sound models for speaker indexing},
  author={Sylvain Meignier and Jean-François Bonastre and St{\'e}phane Igounet},
  booktitle={Odyssey},
  year={2001}
}
This paper presents an iterative process for blind speaker indexing based on a HMM. This process detects and adds speakers one after the other to the evolutive HMM (E-HMM). The use of this HMM approach takes advantage of the different components of AMIRAL automatic speaker recognition system (ASR system: frontend processing, learning, loglikelihood ratio computing) from LIA. The proposed solution reduces the miss detection of short utterances by exploiting all the information (detected speakers… CONTINUE READING
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