Interspeech'2005 - Eurospeech
Handset and channel mismatch degrades the performance of automatic speaker recognition systems significantly. This paper enhances the feature mapping technique by proposing an iterative clustering approach to context model generation which offers an improvement in the performance of feature mapping trained on labelled data and offers the potential to train feature mapping in the absence of correctly labelled background data. The performance of the clustered feature mapping models is demonstrated on an expanded version of the NIST 2003 Extended Data Task (EDT) protocol.
Bibliographic reference. Mason, Michael / Vogt, Robbie / Baker, Brendan / Sridharan, Sridha (2005): "Data-driven clustering for blind feature mapping in speaker verification", In INTERSPEECH-2005, 3109-3112.