Language Identification as Improvement for Lip-Based Biometric Visual Systems

Language has always been one of humanity's defining characteristics. Visual Language Identification (VLI) is a relatively new field of research that is complex and largely understudied. In this paper, we present a preliminary study in which we use linguistic information as a soft biometric trai...

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Bibliographic Details
Published in2023 IEEE International Conference on Image Processing (ICIP) pp. 1570 - 1574
Main Authors Cascone, Lucia, Nappi, Michele, Narducci, Fabio
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.10.2023
Subjects
biometric fusion system
Biometrics (access control)
Image processing
lip biometrics
Lips
Machine learning
Protocols
soft biometrics
speaker identification
Visual Language Identification
Visual systems
Visualization
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Summary:Language has always been one of humanity's defining characteristics. Visual Language Identification (VLI) is a relatively new field of research that is complex and largely understudied. In this paper, we present a preliminary study in which we use linguistic information as a soft biometric trait to enhance the performance of a visual (auditory-free) identification system based on lip movement. We report a significant improvement in the identification performance of the proposed visual system as a result of the integration of these data using a score-based fusion strategy. Methods of Deep and Machine Learning are considered and evaluated. To the experimentation purposes, the dataset called laBial Articulation for the proBlem of the spokEn Language rEcognition (BABELE), consisting of 8 different languages, has been created. It includes a collection of different features of which the spoken language represents the most relevant, while each sample is also manually labelled with gender and age of the subjects.
DOI:10.1109/ICIP49359.2023.10222415