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Investigating the visual lombard effect with gabor based features

  • Waito Chiu
  • , Yan Xu
  • , Andrew Abel
  • , Chun Lin
  • , Zhengzheng Tu
    • Xi'an Jiaotong-Liverpool University
    • Anhui University

    Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

    2 Citations (Scopus)

    Abstract

    The Lombard Effect shows that speakers increase their vocal effort in the presence of noise, and research into acoustic speech, has demonstrated varying effects, depending on the noise level and speaker, with several differences, including timing and vocal effort. Research also identified several differences, including between gender, and noise type. However, most research has focused on the audio domain, with very limited focus on the visual effect. This paper presents a detailed study of the visual Lombard Effect, using a pilot Lombard Speech corpus developed for our needs, and a recently developed Gabor based lip feature extraction approach. Using Kernel Density Estimation, we identify clear differences between genders, and also show that speakers handle different noise types differently.

    Original languageEnglish
    Title of host publicationInterspeech 2020
    PublisherInternational Speech Communication Association
    Pages4606-4610
    Number of pages5
    ISBN (Print)9781713820697
    DOIs
    Publication statusPublished - 2020
    Event21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020 - Shanghai, China
    Duration: 25 Oct 202029 Oct 2020

    Publication series

    NameProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
    Volume2020-October
    ISSN (Print)2308-457X
    ISSN (Electronic)1990-9772

    Conference

    Conference21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020
    Country/TerritoryChina
    CityShanghai
    Period25/10/2029/10/20

    Keywords

    • Gabor Features
    • Lip Features
    • Lombard Effect

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