1. A mobile face-to-face interaction monitoring device, comprising: a conversation group detector for scanning one or more mobile devices in a surrounding area and setting a conversation group; a turn detector for determining turn by using volume topography created based on sound signals detected in the mobile devices in the conversation group, wherein the turn detector comprises: a volume topography builder for creating the volume topography based on the sound signals in the mobile devices in the conversation group, during a training period; and a volume topography matcher for determining current turn by matching current sound signals with the volume topography, after the training period; and a meta-linguistic information processor for extracting meta-linguistic context of interactants in the conversation group based on the turn; wherein the turn is a sound-signal segment where an interactant in the conversation group starts and ends the interactant's speech, and wherein the volume topography is created by using a signature or feature vector of volume value(s) for the sound signals detected, wherein the meta-linguistic context of interactants in the conversation group is extracted by extracting features of the turn and determining the features of the turn categorized as: individual for each of the interactants, including speaking time, a quantity and duration of speech and non-speech turns, and associated statistics, for each of the interactants; relational among the interactants, including orders and frequencies of exchanges of the turns and ratio thereof, among the interactants in the conversation group; and cumulative for one or more conversation sessions and the conversation group, including a number of the interactants in the conversation sessions, a quantity and duration of the conversation sessions, and a quantity and duration of the turns in the conversation sessions and the conversation group.
1. A mobile face-to-face interaction monitoring device, comprising: a conversation group detector for scanning one or more mobile devices in a surrounding area and setting a conversation group; a turn detector for determining turn by using volume topography created based on sound signals detected in the mobile devices in the conversation group, wherein the turn detector comprises: a volume topography builder for creating the volume topography based on the sound signals in the mobile devices in the conversation group, during a training period; and a volume topography matcher for determining current turn by matching current sound signals with the volume topography, after the training period; and a meta-linguistic information processor for extracting meta-linguistic context of interactants in the conversation group based on the turn; wherein the turn is a sound-signal segment where an interactant in the conversation group starts and ends the interactant's speech, and wherein the volume topography is created by using a signature or feature vector of volume value(s) for the sound signals detected, wherein the meta-linguistic context of interactants in the conversation group is extracted by extracting features of the turn and determining the features of the turn categorized as: individual for each of the interactants, including speaking time, a quantity and duration of speech and non-speech turns, and associated statistics, for each of the interactants; relational among the interactants, including orders and frequencies of exchanges of the turns and ratio thereof, among the interactants in the conversation group; and cumulative for one or more conversation sessions and the conversation group, including a number of the interactants in the conversation sessions, a quantity and duration of the conversation sessions, and a quantity and duration of the turns in the conversation sessions and the conversation group. 12. The mobile face-to-face interaction monitoring device according to claim 1 , wherein the volume topography builder creates a quantity of n+1 of the volume topography, where n is a number of the interactants in the conversation group, and wherein: each of the n-quantity of the volume topography created respectively corresponds to each of the n-number of the interactants, and the l-quantity of the volume topography created corresponds to non-speech in the conversation group.