Title
Speaker verification using target and background dependent linear transforms and multi-system fusion
Abstract
This paper describes a GMM-based speaker verification system that uses speaker-dependent background models transformed by speaker-specific maximum likelihood linear transforms to achieve a sharper separation between the target and the non- target acoustic region. The effect of tying, or coupling, Gaus- sian components between the target and the background model is studied and shown to be a relevant factor with respect to the desired operating point. A fusion of scores from multiple sys- tems built on different acoustic features via a neural network with performance gains over linear combination is also pre- sented. The methods are experimentally studied on the 1999 NIST speaker recognition evaluation data.
Year
Venue
Keywords
2001
INTERSPEECH
linear transformation,neural network
Field
DocType
Citations 
Speaker verification,Pattern recognition,Computer science,Fusion,Speech recognition,Speaker recognition,Natural language processing,Artificial intelligence,Speaker diarisation
Conference
12
PageRank 
References 
Authors
2.31
4
3
Name
Order
Citations
PageRank
Jiri Navratil131431.36
Upendra V. Chaudhari229734.63
Ganesh N. Ramaswamy321325.72