Effective lip localization and tracking for achieving multimodal speech recognition

Chuan Ooi Wei, Changwon Jeon, Kihyeon Kim, David K. Han, Hanseok Ko

Research output: Contribution to conferencePaperpeer-review

9 Citations (Scopus)

Abstract

Effective fusion of acoustic and visual modalities in speech recognition has been an important issue in Human Computer Interfaces, warranting further improvements in intelligibility and robustness. Speaker lip motion stands out as the most linguistically relevant visual feature for speech recognition. In this paper, we present a new hybrid approach to improve lip localization and tracking, aimed at improving speech recognition in noisy environments. This hybrid approach begins with a new color space transformation for enhancing lip segmentation. In the color space transformation, a PCA method is employed to derive a new one dimensional color space which maximizes discrimination between lip and non-lip colors. Intensity information is also incorporated in the process to improve contrast of upper and corner lip segments. In the subsequent step, a constrained deformable lip model with high flexibility is constructed to accurately capture and track lip shapes. The model requires only six degrees of freedom, yet provides a precise description of lip shapes using a simple least square fitting method. Experimental results indicate that the proposed hybrid approach delivers reliable and accurate localization and tracking of lip motions under various measurement conditions.

Original languageEnglish
Pages90-93
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI - Seoul, Korea, Republic of
Duration: 2008 Aug 202008 Aug 22

Other

Other2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI
Country/TerritoryKorea, Republic of
CitySeoul
Period08/8/2008/8/22

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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