The disclosure herein describes a system for calculating meeting inclusion metrics including insights and recommendations. Meeting data associated with one or more meetings attended by at least one participant remotely is converted into anonymized meeting data for inclusivity metric analysis. An inclusivity insights manager generates inclusivity metrics associated with inclusive behavior and language occurring during meetings to measure the level of inclusivity. The inclusivity metrics include attendee participation metrics measuring an amount of participation by each meeting attendee, participation in-person versus participation remotely, concurrent speech indicating attendees may be talking over one another or other interruptions occurring during meetings. Inclusivity metric data includes insights and actionable recommendations to improve inclusivity at future meetings provided at an individual level, group level or organizational level. The inclusivity insights can also include percentage metric values, graphs, feedback, and other metric-related information for improving participation by meeting attendees.

Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

A system for capturing behavioural data in order to influence an interpersonal interaction. In one aspect, the system assists n the training of an entity whose role is to engage in such interpersonal interactions. In this aspect, the collected information may be used to judge performance, and/or adapt or improve approach to future interactions, In another aspect, the system may assist with a live interaction, i.e. to provide feedback in an ongoing conversation. The system comprises a wearable device having (i) a data collection device configured to capture behavioural data during the interpersonal interaction, (ii) a microphone configured to capture audio data during the interpersonal interaction, and (ill) an analysis module arranged to extract emotional state information and content data, and use that extracted data to evaluate an interaction quality metric to obtain an interaction score for the interpersonal interaction.

A system for capturing behavioural data in order to influence an interpersonal interaction. In one aspect, the system assists n the training of an entity whose role is to engage in such interpersonal interactions. In this aspect, the collected information may be used to judge performance, and/or adapt or improve approach to future interactions, In another aspect, the system may assist with a live interaction, i.e. to provide feedback in an ongoing conversation. The system comprises a wearable device having (i) a data collection device configured to capture behavioural data during the interpersonal interaction, (ii) a microphone configured to capture audio data during the interpersonal interaction, and (ill) an analysis module arranged to extract emotional state information and content data, and use that extracted data to evaluate an interaction quality metric to obtain an interaction score for the interpersonal interaction.

A method and apparatus for generating an interaction record, and a device and a medium are provided. The method includes: firstly, from a multimedia data stream, collecting behavior data, represented by the multimedia data stream, of a user, wherein the behavior data includes voice information and/or operation information; and then, on the basis of the behavior data, generating interaction record data corresponding to the behavior data. According to the technical solution, by means of collecting voice information and/or operation information from a multimedia data stream, and generating interaction record data on the basis of the voice information and the operation information, an interacting user can determine interaction information by using the interaction record data, and the interaction efficiency of the interacting user is improved, thereby also improving the user experience.

A method and apparatus for generating an interaction record, and a device and a medium are provided. The method includes: firstly, from a multimedia data stream, collecting behavior data, represented by the multimedia data stream, of a user, wherein the behavior data includes voice information and/or operation information; and then, on the basis of the behavior data, generating interaction record data corresponding to the behavior data. According to the technical solution, by means of collecting voice information and/or operation information from a multimedia data stream, and generating interaction record data on the basis of the voice information and the operation information, an interacting user can determine interaction information by using the interaction record data, and the interaction efficiency of the interacting user is improved, thereby also improving the user experience.

A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.

System, electronic device, and related methods, in particular a method of operating a system comprising an electronic device is disclosed, the method comprising obtaining one or more audio signals including a first audio signal of a first conversation; determining a first conversation period of the first conversation, the first conversation period having a first duration; determining first conversation metric data including a first conversation metric based on the first conversation period; determining a second conversation period of the first conversation different from the first conversation period, the second conversation period having a second duration; determining second conversation metric data including a second conversation metric based on the second conversation period; determining a first performance metric based on a change between the first conversation metric data and the second conversation metric data; outputting, via the interface of the electronic device, the first performance metric.