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
    • General Computer Science
    • Electrical and Electronic Engineering

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