QUT ePrints

A Posterior Approach for Microphone Array Based Speech Recognition

Wang, Dong , Himawan, Ivan, Frankel, Joe, & King, Simon (2008) A Posterior Approach for Microphone Array Based Speech Recognition. In Interspeech 2008, 22-26 September 2008, Brisbane, Australia.

[img] PDF (205kB)
Available to QUT staff and students only | Request a copy from author

    Abstract

    Automatic speech recognition (ASR) is difficult in environments such as multiparty meetings because of adverse acoustic conditions: background noise, reverberation and cross-talk. Microphone arrays can increase ASR accuracy dramatically in such situations. However, most existing beamforming techniques use time-domain signal processing theory and are based on a geometric analysis of the relationship between sources and microphones. This limits their application, and leads to performance degradation when the geometric properties are unavailable, or heterogeneous channels are used. We present a new posterior-based approach for microphone array speech recognition. Instead of enhancing speech signals, we enhance posterior phone probabilities which are used in a tandem ANN-HMM system. Significant improvements were achieved over a single channel baseline. Combining beamforming and our method is significantly better than beamforming alone, especially in a moving speakers scenario.

    Impact and interest:

    0 citations in Scopus
    Search Google Scholar™
    0 citations in Web of Science®

    Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

    These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

    Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

    ID Code: 15341
    Item Type: Conference Paper
    Additional URLs:
    Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
    Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > QUT Faculties & Divisions > Faculty of Science and Technology
    Past > Institutes > Information Security Institute
    Copyright Owner: Copyright 2008 The International Speech Communication Association (ISCA)
    Deposited On: 27 Oct 2008
    Last Modified: 01 Mar 2012 11:00

    Export: EndNote | Dublin Core | BibTeX

    Repository Staff Only: item control page