Publication detail

Independent Component Analysis and MLLR Transforms for Speaker Identification

CUMANI, S. PLCHOT, O. KARAFIÁT, M.

Original Title

Independent Component Analysis and MLLR Transforms for Speaker Identification

English Title

Independent Component Analysis and MLLR Transforms for Speaker Identification

Type

conference paper

Language

en

Original Abstract

This paper describes the use of of Independent Component Analysis (ICA) and Principal Component Analysis (PCA) techniques to reduce the dimensionality of high-level LVCSR features.

English abstract

This paper describes the use of of Independent Component Analysis (ICA) and Principal Component Analysis (PCA) techniques to reduce the dimensionality of high-level LVCSR features.

Keywords

Speaker Recognition, MLLR, ICA, PLDA, SVM

RIV year

2012

Released

25.03.2012

Publisher

IEEE Signal Processing Society

Location

Kyoto

ISBN

978-1-4673-0044-5

Book

Proc. International Conference on Acoustics, Speech, and Signal P

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

4365

Pages to

4368

Pages count

4

URL

Documents

BibTex


@inproceedings{BUT91483,
  author="Sandro {Cumani} and Oldřich {Plchot} and Martin {Karafiát}",
  title="Independent Component Analysis and MLLR Transforms for Speaker Identification",
  annote="This paper describes the use of of Independent Component Analysis (ICA) and
Principal Component Analysis (PCA) techniques to reduce the dimensionality of
high-level LVCSR features.",
  address="IEEE Signal Processing Society",
  booktitle="Proc. International Conference on Acoustics, Speech, and Signal P",
  chapter="91483",
  doi="10.1109/ICASSP.2012.6288886",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Signal Processing Society",
  year="2012",
  month="march",
  pages="4365--4368",
  publisher="IEEE Signal Processing Society",
  type="conference paper"
}