Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The availability of mobile sociometric sensors allows Computer-Supported Cooperative Work (CSCW) designers the possibility to enhance online meeting support through automatic recognition of conversational context.  addresses the task of discriminating one conversational context against another, specifically brainstorming from decision-making interactions using easily computable nonverbal behavioral cues.  hypothesize that the difference in the dynamics beten brainstorming and decision-making discussions is significant and measurable using speech activity based nonverbal cues.  employ a set of nonverbal cues to characterize the entire group by the aggregation (both temporal and person-wise) of their nonverbal behavior. Our results on a dataset collected using privacy-sensitive sociometric badges show that the floor-occupation patterns in a brain-storming interaction are different from a decision-making interaction and  can obtain a discrimination accuracy as high as 87.5%.
['Dinesh Babu Jayagopi', 'Taemie Kim', 'Alex Pentland', 'Daniel Gatica-Perez']
I am writing a research paper on a idea Recognizing conversational context in group interaction using privacy-sensitive mobile sensors
[{"from": "human", "value": "I am writing a research paper on a idea Recognizing conversational context in group interaction using privacy-sensitive mobile sensors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The availability of mobile sociometric sensors allows Computer-Supported Cooperative Work (CSCW) designers the possibility to enhance online meeting support through automatic recognition of conversational context.  addresses the task of discriminating one conversational context against another, specifically brainstorming from decision-making interactions using easily computable nonverbal behavioral cues.  hypothesize that the difference in the dynamics beten brainstorming and decision-making discussions is significant and measurable using speech activity based nonverbal cues.  employ a set of nonverbal cues to characterize the entire group by the aggregation (both temporal and person-wise) of their nonverbal behavior. Our results on a dataset collected using privacy-sensitive sociometric badges show that the floor-occupation patterns in a brain-storming interaction are different from a decision-making interaction and  can obtain a discrimination accuracy as high as 87.5%."}]