Mobile Call Speech Analysis for Predictive Follow-Up Actions
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Solution Overview
Problem
Existing mobile terminals lack the ability to propose user actions in advance during ongoing calls, disrupting the conversation as users often need to perform additional tasks like checking schedules or messages, which is inconvenient and inefficient.
Innovation Solution
A call service processing apparatus and method that analyzes phone conversation information through speech recognition, predicts follow-up actions based on conversation analysis, and activates corresponding applications or functions in the mobile terminal, such as scheduling or spam registration, during an ongoing call.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the mobile terminal provides limited functions during a call to maintain simplicity, then the device complexity is reduced, but the user cannot perform necessary follow-up actions without interrupting the conversation
Solution Approach 1:
The system performs speech recognition and analyzes conversation content during the call to predict what follow-up actions the user will need. Applications are activated in advance based on this prediction, so when the user needs to check schedules or messages, these functions are already ready and waiting, eliminating the need to interrupt the conversation.
Solution Approach 2:
The mobile terminal automatically performs speech recognition, conversation analysis, and application activation without requiring user intervention. The system serves itself by autonomously determining when to activate follow-up applications based on analyzed conversation patterns, reducing the operational burden on the user.
2Adaptability or versatility
If the mobile terminal activates multiple applications during a call to provide comprehensive services, then the versatility is improved, but the ease of operation deteriorates due to increased complexity
Solution Approach 1:
The system continuously monitors conversation content through speech recognition during the call and uses this feedback to dynamically determine which follow-up applications should be activated. This real-time feedback mechanism allows the terminal to adaptively provide comprehensive services while maintaining simple operation, as applications are activated automatically based on conversation context rather than requiring complex user commands.
3Productivity
If the user manually activates applications during a call to perform follow-up actions, then the productivity is maintained, but the loss of time increases due to conversation interruption
Solution Approach 1:
The system predicts and activates follow-up applications during the ongoing call based on speech recognition analysis, so that when the user needs to perform actions like checking schedules or messages, these applications are already activated and ready. This eliminates the time loss associated with interrupting the conversation to manually activate applications.
4Use of energy by moving object
If the mobile terminal disables display and touch input functions during a call to save battery power, then the energy consumption is reduced, but the ease of operation worsens when users need to interact with the interface
Solution Approach 1:
The system activates follow-up applications and prepares their interfaces during the call based on predicted user needs. This allows the display and touch input functions to remain disabled during the call (saving battery), yet when users need to interact with follow-up actions, the applications are already prepared and can be accessed efficiently when the terminal is brought away from the ear.
Data Source
AI summary
An apparatus and method for processing call services in a mobile terminal are provided. The method for processing call services in a mobile terminal includes entering into, when a call is generated, a call handling mode, recognizing and analyzing voice signals sent and received in the call to produce speech analysis information, detecting a state change of the mobile terminal using a sensing unit to produce user behavior information, and predicting, when a state change of the mobile terminal is detected, an application corresponding to the speech analysis information, and activating the application as a follow-up service.