Mobile device executing face-to-face interaction monitoring, method of monitoring face-to-face interaction using the same, and interaction monitoring system including the same, and mobile interaction monitoring application executed on the same
First Claim
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, andwherein 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.
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Accused Products
Abstract
Disclosed herein is a mobile face-to-face interaction monitoring device and method using the same and system including the same, for supporting accurate and efficient turn monitoring. One embodiment of the mobile face-to-face interaction monitoring device may comprise a conversation group detector for scanning mobile devices in a surrounding area and setting a conversation group, a turn detector for determining (conversational) turn using volume topography created based on sound signals detected in the mobile devices in the conversation group, and a meta-linguistic information processor for extracting meta-linguistic context of participants or interactants in the conversation group based on the turn. Other embodiments are described and shown.
6 Citations
32 Claims
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1. A mobile face-to-face interaction monitoring device, comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A mobile face-to-face interaction monitoring method, comprising:
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scanning one or more mobile devices in a surrounding area and setting a conversation group; detecting sound signals in the mobile devices in the conversation group, relative to differences in positions of the mobile devices; creating volume topography based on the sound signals for each interactant in the conversation group; determining turn by using the volume topography; and extracting meta-linguistic context of interactants in the conversation group based on the turn, wherein the turn is a sound-signal segment where each interactant in the conversation group starts and ends the interactant'"'"'s speech, wherein the volume topography is created by using a signature or feature vector of volume value(s) for the sound signals detected, and wherein the creating the volume topography based on the sound signals is performed by creating a quantity of n+l 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 or silent turns in the conversation group. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. An interaction monitoring system, comprising:
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a first mobile device, which determines turn, and at least one second mobile device, which receives the turn determined from the first mobile device; wherein the first mobile device comprises; a first 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 for interactants in the conversation group by using volume topography created by using a signature or feature vector of volume value(s) based on sound signals detected in the mobile devices, relative to different positions of the first and second mobile devices, and represented as a set of sound-signal signatures for each of the interactants, and a first meta-linguistic information processor for extracting meta-linguistic context of the interactants in the conversation group based on the turn; and
wherein the second mobile device comprises;a second conversation group detector for scanning the mobile devices in the surrounding area and setting the conversation group, and a second meta-linguistic information processor for extracting the meta-linguistic context of the interactants in the conversation group based on the turn received from the first mobile device; wherein the volume topography is created by using a transformed vector P″
(t),wherein the transformed vector P″
(t) is defined as
P″
(t)=D(t)*P′
(t)={D(t,1)*p(t,1)/E(t),D(t,2)*p(t,2)/E(t), . . . ,D(t,np)*p(t,np)/E(t)},where a decibel D(t) measured on the mobile device i, at the given time t, is defined as D(t,i)=20*log 10 (p(t,i)/p.ref), where p.ref is a standard reference sound pressure level, and where a normalized feature vector P′
(t) is defined as P′
(t)=P(t)/E(t), where E(t) is an average of a feature vector P(t),where the feature vector P(t) is defined as P(t)=(p(t,1), p(t,2), . . . , p(t,np)), where p(t, i) is an average of a square of the sound signals in each mobile device i of the mobile devices at a given time t, and np is a quantity of the mobile devices in the conversation group.
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Specification