This paper proposes a system called Neary that detects conversational fields based on similarity of auditory situation among users. The similarity of auditory situation between each pair of the users is measured by the similarity of frequency property of sound captured by head-worn microphones of the individual users. Neary is implemented with a simple algorithm and runs on portable PCs. Experimental result shows Neary can successfully distinguish groups of conversations and track dynamic changes of them. This paper also presents two examples of Neary deployment to detect user contexts during experience sharing in touring at the zoo and attending an academic conference.