The liveliness of speech has also been associated with the perception of enthusiasm.
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The role of prosody in delivering successful presentations has been highlighted in several manuals of public speaking, where it is advised that a presenter should have a lively voice, with variations in intonation, rhythm and loudness ( Lamerton, 2001 Grandstaff, 2004).
Several studies have elicited audio and visual cues that are linked to presentation quality.
This study moves toward a rich assessment system by taking into account multimodal behavior. Within this context, automatic assessment of presentation skills can be viewed as an emerging assessment model to measure presentation skills that addresses the burdens of time and cost, given that, until recently, this kind of assessment has relied on human ratings ( Schreiber et al., 2012 Ward, 2013). A challenge in education and training has been to develop the ability to deliver skill assessments in a personalized, reliable, cost-effective, and scalable manner. Public speaking is a form of communication that requires a distinctive skills set, including self-awareness, self-control, organization, and critical thinking, which are reflected in multimodal, verbal and non-verbal elements of information delivery. In this framework, presentation skills are considered as part of one's organizational and communication skills. Presentation skills are a competency that can be viewed as part of transversal skills, i.e., core skills, such as critical and creative thinking, problem-solving, interpersonal communication and collaboration skills that a person needs to develop to be successful in the twenty-first century society and workplaces ( Bellanca and Brandt, 2010). Applications of the method to provision of feedback to teachers and trainees are discussed. The fusion of audio and video data provides the best results for eye contact. The video data representation provides the best results for presentation of relevant information with good pronunciation, usage of language according to audience, and maintenance of adequate voice volume for the audience. The audio representation provides the best prediction results for self-confidence and enthusiasm, posture and body language, structure and connection of ideas, and overall presentation delivery.
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This representation is also used to analyse video segments within a full video presentation in terms of several characteristics of the presenter's performance. The proposed data representation is generated unsupervised using low-level audiovisual descriptors and self-organizing mapping and used for video classification. While most approaches have employed a two step strategy consisting of detecting multiple events followed by classification, which involve the annotation of data for building the different event detectors and generating a data representation based on their output for classification, our method does not require event detectors. In this study, we propose an automatic scoring system for presentation delivery skills using a novel active data representation method to automatically rate segments of a full video presentation. These methods include assessment of the trainee's oral presentation delivery skills which may be accomplished through automatic understanding and processing of social and behavioral cues displayed by the presenter. In recent years, researchers have started to investigate automatic methods to support public speaking skills training. Public speaking is an important skill, the acquisition of which requires dedicated and time consuming training.
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