README.txt
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This recipe replaces iVectors used in the v1 recipe with embeddings extracted
from a deep neural network. In the scripts, we refer to these embeddings as
"xvectors." The recipe in local/nnet3/xvector/tuning/run_xvector_1a.sh is
closesly based on the following paper:
@inproceedings{snyder2018xvector,
title={X-vectors: Robust DNN Embeddings for Speaker Recognition},
author={Snyder, D. and Garcia-Romero, D. and Sell, G. and Povey, D. and Khudanpur, S.},
booktitle={2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year={2018},
organization={IEEE},
url={http://www.danielpovey.com/files/2018_icassp_xvectors.pdf}
}
The recipe uses the following data for system development. This is in
addition to the NIST SRE 2016 dataset used for evaluation (see ../README.txt).
Corpus LDC Catalog No.
SWBD2 Phase 1 LDC98S75
SWBD2 Phase 2 LDC99S79
SWBD2 Phase 3 LDC2002S06
SWBD Cellular 1 LDC2001S13
SWBD Cellular 2 LDC2004S07
SRE2004 LDC2006S44
SRE2005 Train LDC2011S01
SRE2005 Test LDC2011S04
SRE2006 Train LDC2011S09
SRE2006 Test 1 LDC2011S10
SRE2006 Test 2 LDC2012S01
SRE2008 Train LDC2011S05
SRE2008 Test LDC2011S08
SRE2010 Eval LDC2017S06
Mixer 6 LDC2013S03
The following datasets are used in data augmentation.
MUSAN http://www.openslr.org/17
RIR_NOISES http://www.openslr.org/28