Detail publikace
Simplification and optimization of I-Vector Extraction
GLEMBEK, O. BURGET, L. KENNY, P. KARAFIÁT, M. MATĚJKA, P.
Originální název
Simplification and optimization of I-Vector Extraction
Anglický název
Simplification and optimization of I-Vector Extraction
Jazyk
en
Originální abstrakt
We managed to reduce the memory requirements and processing time for the i-vector extractor training so that higher dimensions can be now used while retaining the recognition accuracy. As for i-vector extraction, we managed to reduce the complexity of the algorithm with sacrificing little recognition accuracy, which makes this technique usable in small-scale devices.
Anglický abstrakt
We managed to reduce the memory requirements and processing time for the i-vector extractor training so that higher dimensions can be now used while retaining the recognition accuracy. As for i-vector extraction, we managed to reduce the complexity of the algorithm with sacrificing little recognition accuracy, which makes this technique usable in small-scale devices.
Dokumenty
BibTex
@inproceedings{BUT76376,
author="Ondřej {Glembek} and Lukáš {Burget} and Patrick {Kenny} and Martin {Karafiát} and Pavel {Matějka}",
title="Simplification and optimization of I-Vector Extraction",
annote="We managed to reduce the memory requirements and processing time for the i-vector
extractor training so that higher dimensions can be now used while retaining the
recognition accuracy. As for i-vector extraction, we managed to reduce the
complexity of the algorithm with sacrificing little recognition accuracy, which
makes this technique usable in small-scale devices.",
address="IEEE Signal Processing Society",
booktitle="Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011",
chapter="76376",
edition="NEUVEDEN",
howpublished="print",
institution="IEEE Signal Processing Society",
year="2011",
month="may",
pages="4516--4519",
publisher="IEEE Signal Processing Society",
type="conference paper"
}