Call Tuning Model Adjusts Parameters via User Input
Solution Overview
Problem
Conventional communication systems lack the ability for users to provide feedback during calls to improve call quality, relying solely on objective measurable factors without user input.
Innovation Solution
The system receives user input data, such as audio stickers, masks, reactions, emojis, or doodles, during calls and uses this data as input to a call-tuning model to modify call parameters, such as codecs, bit rates, or echo cancellation settings, to enhance call quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If objective measurable parameters are used to control call quality, then call parameters can be adjusted based on technical metrics, but user perception of call quality cannot be accurately reflected
Solution Approach 1:
The system implements feedback by collecting user inputs during calls (such as audio stickers, masks, reactions, emojis, or doodles) and using these inputs to automatically adjust call parameters. The call-tuning model processes user feedback in real-time to modify codecs, bit rates, or echo cancellation settings, creating a closed-loop system where user perception directly influences system behavior.
Solution Approach 2:
The patent introduces an intermediary call-tuning model that translates subjective user inputs into objective call parameter adjustments. This intermediary component bridges the gap between user perception and technical call quality metrics, converting non-technical user expressions into actionable parameter modifications without requiring users to understand technical details.
2Adaptability or versatility
If user input is collected and processed in real-time during calls, then call quality can be optimized based on user perception, but system complexity increases
Solution Approach 1:
The system employs self-service by enabling automatic call parameter adjustment without requiring manual user configuration. The call-tuning model autonomously processes user inputs and makes real-time parameter modifications, eliminating the need for users to manually adjust technical call settings while still achieving personalized optimization.
Solution Approach 2:
The patent implements parameter changes by dynamically modifying call parameters (codecs, bit rates, echo cancellation settings) based on processed user inputs. The call-tuning model adjusts these parameters in real-time to optimize call quality according to user perception, transforming static system configuration into dynamic adaptive behavior.
3Ease of operation
If conventional call parameter adjustment methods are used, then system operation is simple, but call quality optimization based on user feedback is not achieved
Solution Approach 1:
The system implements feedback by collecting user inputs during calls (such as audio stickers, masks, reactions, emojis, or doodles) and using these inputs to automatically adjust call parameters. The call-tuning model processes user feedback in real-time to modify codecs, bit rates, or echo cancellation settings, creating a closed-loop system where user perception directly influences system behavior.
Data Source
AI summary
Techniques for using user input to tune calls include receiving communication data from a first client device, at a server, directed to a second client device during a call between the first client device and the second client device; forwarding the communication data to the second device; receiving from one of the first client device or the second client device, first user input data; using the first user input data as an input to a call-tuning model; and modifying a call parameter of the call according to output from the call-tuning model in response to the first user input. Other embodiments are described and claimed.