• DocumentCode
    699147
  • Title

    On improving Voice Activity Detection by fuzzy logic rules: Case of coherence based features

  • Author

    Ben Jebara, Sofia ; Ben Amor, Taha

  • Author_Institution
    Dept. de Math. Appl., Signal et Commun., Ecole Super. des Commun. de Tunis, Tunis, Tunisia
  • fYear
    2004
  • fDate
    6-10 Sept. 2004
  • Firstpage
    725
  • Lastpage
    728
  • Abstract
    In this paper, we investigate the use of fuzzy logic for Voice Activity Detection (VAD). The feature extraction part is based on coherence measure between the noisy speech and its prediction residue. The decision part uses fuzzy logic rules instead of classical thresholding tools. Different fuzzy logic models are developed in order to track noise characteristics. The performances of the algorithm are compared to that of ITU-T G.729B VAD and UMTS 3G TS 26.094 VAD in various conditions. The results show that the proposed algorithm has globally better performances than G.729B and presents moderate improvement when compared to UMTS 3G TS 26.094 VAD.
  • Keywords
    feature extraction; fuzzy logic; fuzzy set theory; speech processing; ITU-T G.729B; UMTS 3G TS 26.094; VAD; coherence measure; feature extraction; fuzzy logic models; fuzzy logic rules; noisy speech; prediction residue; voice activity detection; Abstracts; GSM; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2004 12th European
  • Conference_Location
    Vienna
  • Print_ISBN
    978-320-0001-65-7
  • Type

    conf

  • Filename
    7079677