ELAN-Based Multimodal Analysis of Non-linguistic Features in the TED Speech for the Education of Public Speaking Ability

Abstract

Non-linguistic features, conveying meaning and speech as symbolic resources, is an activity that involves a wealth of modes, where non-linguistic symbols can play an important role. Thus, under the guidance of dynamic multimodal analysis framework as well as the video analysis tool ELAN, an analysis of the speech by Han Xue, a famous actor and singer in China was carried out. Findings are overused movements with hands, using speech rhyme for attracting attention, as well as single facial expression. Some non-linguistic resources are contributing to meaning-making, yet Han fails to use them properly. Besides, when relations of modes in Han's speech are investigated, it turns out that highlighting relation is the most frequent one, and body movement is the least appropriately used resources. Regarding to the education of English speaking ability, learners might adopt appropriately non-linguistic features through multiple relations of modes.