Cross-Device Companion App for Phone Call Context
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Solution Overview
Problem
Conventional phone call management systems fail to provide adequate context for incoming calls, requiring users to manually search for relevant information and applications, leading to inefficient context switching and potential missed actions.
Innovation Solution
The system identifies the caller's intention and relevant actions through speech-to-text transcription, automatically surfacing relevant content and applications on connected devices during the call, and generating a to-do list for post-call actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional caller-id and identifying information are used to provide context for incoming calls, then the recipient can identify the caller and decide whether to answer, but the recipient still lacks comprehensive context about the call purpose and relevant information, requiring manual searching and context switching
Solution Approach 1:
The system performs preliminary actions by automatically retrieving and preparing relevant information, documents, and applications before the user needs them. When a call is incoming, the system proactively gathers context about the caller, previous interactions, and potentially relevant documents or applications, making this information ready for immediate display without requiring the user to manually search for it.
Solution Approach 2:
The system serves itself by automatically identifying the caller, retrieving relevant information, and preparing contextual data without human intervention. The contextual information system autonomously queries databases, retrieves documents, identifies relevant applications, and organizes this information for display, eliminating the need for the user to manually perform these information-gathering tasks.
2Ease of operation
If the system automatically retrieves and presents contextual information, documents, and applications during phone calls, then the recipient gains comprehensive context without manual searching, but the system complexity increases
Solution Approach 1:
The patent introduces a contextual information system as an intermediary layer between the user and the various information sources. This mediator automatically queries multiple databases, retrieves documents, identifies relevant applications, and synthesizes this information into a unified contextual display. The intermediary handles the complexity of coordinating multiple data sources and processing logic, while the user simply receives the organized contextual information without needing to understand or manage the underlying system complexity.
3Reliability
If caller identification information is displayed to help users decide whether to answer, then users can make informed decisions and save time on identification, but users still experience context switching and lack of information about call relevance
Solution Approach 1:
The contextual information system performs multiple functions within a single integrated framework. It not only displays caller identification information but also retrieves relevant documents, identifies appropriate applications, summarizes previous interactions, and presents all this contextual information together. This multi-functional approach allows the system to adapt to different call scenarios and provide comprehensive context rather than just basic identification, enhancing both reliability and contextual flexibility.
Data Source
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AI summary
Example apparatus and methods concern establishing context for a phone call. A computing device is controlled to display content and applications that are relevant for the call during the call. A party on the call is identified using data received from a phone used by the party. The relevant content and the relevant application are identified using actions (e.g., purchase to make, call to make) and intentions (e.g., family matter, business matter) identified in text provided in a text-based transcript of the call. The text-based transcript is provided in real time by a natural language processing (NLP) service during the call. The devices are controlled to selectively present the relevant content and the relevant application to make the call more automated and more productive. A to-do list is automatically generated based on the intentions, the actions, and on subject matter or content discussed or accessed during the call.