Dynamic Conversation Alerts Through Categorized Phrase Matching
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Solution Overview
Problem
Current digital communication platforms lack the ability to provide dynamic conversation alerts, such as indicators or alerts triggered in uttered sentences in specific categories like 'budget' or 'intent to buy', and do not allow users to define alert phrases or trigger automatic actions during remote meetings.
Innovation Solution
A system that presents a user interface for users to submit alert phrases associated with categories, receives a communication session transcript, determines relatedness between utterances and alert phrases, and transmits related categories with timestamps for real-time alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time analysis of communication sessions is implemented to provide dynamic alerts, then communication analysis efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining alert phrases and categories before the communication session begins. Users configure what phrases to monitor and what categories they belong to in advance, so that during the actual communication session, the system only needs to match utterances against these pre-configured parameters, significantly reducing real-time processing complexity
Solution Approach 2:
The system segments the communication analysis task into distinct components: transcript generation, utterance segmentation, alert phrase matching, and alert generation. Each component handles a specific aspect of the analysis independently, making the overall system more manageable and easier to implement despite the complexity of real-time analysis
2Loss of time
If automatic alert actions are triggered during communication sessions, then response time is improved, but control precision deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms where users can review generated alerts and adjust the alert phrases and categories. The system learns from user interactions and feedback, refining its matching accuracy over time. This allows automatic triggering to maintain fast response times while improving control precision through continuous optimization based on user feedback
Solution Approach 2:
The system allows dynamic adjustment of parameters such as alert phrase definitions, category assignments, and matching thresholds. Users can modify these parameters based on their specific needs and observe the effects, enabling fine-tuning of the balance between automated response speed and precision without requiring complete system redesign
Data Source
AI summary
Methods and systems provide for dynamic conversation alerts within a communication session. In one embodiment, the system presents, to a client device associated with a user of a communication platform, a user interface (“UI”) including a prompt for the user to submit one or more alert phrases, each alert phrase being associated with a category; receives, from the client device, a list of submitted alert phrases; and receives a transcript of a communication session between participants. For each utterance in the transcript, the system determines whether one or more predictions of relatedness are present between the utterance and one or more alert phrases from the list of submitted alert phrases. The system then transmits, to the client device, a list of related categories, each related category including one or more timestamps of utterances for which a prediction of relatedness is present for an alert phrase associated with that category.