A closed-form solution of linear spectral transformation for robust speech recognition

Donghyun Kim, Dongsuk Yook

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The maximum likelihood linear spectral transformation (ML-LST) using a numerical iteration method has been previously proposed for robust speech recognition. The numerical iteration method is not appropriate for real-time applications due to its computational complexity. In order to reduce the computational cost, the objective function of the ML-LST is approximated and a closed-form solution is proposed in this paper. It is shown experimentally that the proposed closed-form solution for the ML-LST can provide rapid speaker and environment adaptation for robust speech recognition.

Original languageEnglish
Pages (from-to)454-456
Number of pages3
JournalETRI Journal
Volume31
Issue number4
DOIs
Publication statusPublished - 2009 Aug

Keywords

  • Closed-form solution
  • Environment adaptation
  • Linear spectral transformation
  • Speech recognition

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Computer Science(all)
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A closed-form solution of linear spectral transformation for robust speech recognition'. Together they form a unique fingerprint.

Cite this