The Challenge of Preserving Captured Sign Language Data in Human Avatar Models
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Detalles
Language attitude studies seek to reveal speech communities’ underlying attitudes and to study certain contexts that sustain idealization or stigmatization of language varieties. Methodology for studying language attitudes typically includes language judgment tasks based on audio recordings (CampbellKibler, 2010). While audio recordings can be obtained without visual markers, the same is not true of the video recordings required to capture sign language. As a result, it is often difficult to distinguish language judgments from social ones. Hill (2012) found that research informants were often reserved with their language judgments in order to avoid looking judgmental about signers’ appearance. Motion capture and animation technology address this problem by masking sign models’ identities with avatars.