Generative Communication Event Effects for Smoother Join and Exit Alerts
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Solution Overview
Problem
Participants joining or leaving online communication sessions often go unnoticed or are announced abruptly, disrupting the flow and context of the session.
Innovation Solution
Generative communication session event effects, such as intros and outros, are created using a generative machine learning model to incorporate participant likenesses and background information, providing advance indications of arrivals and departures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional announcement methods are used for participant entry/exit, then information is conveyed, but the session flow is disrupted
Solution Approach 1:
The system displays an advance indication (e.g., countdown timer) before the participant actually joins or leaves. This preliminary action allows other participants to prepare mentally and contextually, reducing the shock of sudden changes while ensuring the information is conveyed. The event effect plays simultaneously or just before the actual event occurs.
Solution Approach 2:
The announcement system transitions from static, abrupt notifications to dynamic, timed sequences. The event effect duration and timing are adjusted based on session context, creating a flexible announcement mechanism that adapts to different situations while maintaining session flow.
2Productivity
If no announcement is made for participant entry/exit, then session flow is maintained, but participants go unnoticed
Solution Approach 1:
The system implements periodic visual or auditory cues during the event effect that draw attention to the joining or leaving participant. These periodic elements (e.g., pulsing indicators, rhythmic audio cues) ensure the information is noticed without requiring continuous disruptive interruptions.
3Loss of information
If detailed information is provided about participant changes, then contextual understanding is improved, but the announcement becomes more disruptive
Solution Approach 1:
The system provides different levels of information to different participants based on their role and context. The host receives comprehensive information, while other participants receive streamlined notifications. The event effect itself provides contextual information (participant name, avatar, background) in a visually integrated manner rather than through disruptive audio announcements.
Data Source
AI summary
In examples, an “event effect” is an introductory segment that is an intro for a communication participant and/or an exit segment that is an outro for a communication participant. At least a part of the segment may be produced using a generative machine learning model, for example to incorporate a likeness of the participant into the segment, to generate a segment that is based on or otherwise relates to a user's background, and/or to generate at least a part of the segment according to a prompt, among other examples. In some instances, an event effect is displayed in advance of the arrival or departure of a communication participant and/or an advance indication is presented prior to displaying the event effect. As a result, other participants are alerted that a participant will soon join or leave the communication session accordingly.