Bot Group Messaging Voice Library Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current messaging services lack the ability to effectively integrate and manage both user-oriented and group-oriented bots within group messaging environments, limiting their functionality and interaction capabilities.
Innovation Solution
A method and system for a group messaging service that identifies and processes messages sent to bots, utilizing speech-to-text conversion and natural language processing to execute actions, allowing for enhanced text production and audio replies, with options for shared or per-user bot configurations for various tasks and commercial services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If general-purpose bots are used to provide wide range of services, then service versatility is improved, but the ability to perform specific group messaging tasks efficiently deteriorates
Solution Approach 1:
The patent segments the bot ecosystem into specialized components: user bots handle individual user interactions while group bots manage group-level operations. This segmentation allows each bot type to be optimized for its specific function, resolving the contradiction between versatility and task execution efficiency by distributing capabilities across specialized agents rather than relying on a single general-purpose bot to handle all tasks.
2Device complexity
If a single bot handles all group messaging tasks, then system complexity is reduced, but the functionality and interaction capabilities deteriorate
Solution Approach 1:
The patent implements multi-functionality through the introduction of a bot gateway that mediates between user bots and group bots. The gateway provides universal interface capabilities, handling message routing, bot identification, and interaction coordination. This allows the system to maintain low complexity at the interface level while supporting diverse interaction capabilities through multiple specialized bot types working together.
3Measurement precision
If bot-specific voice libraries are implemented for processing recorded audio, then speech recognition accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies local quality by implementing bot-specific voice libraries that are tailored to each bot's functional domain. User bots have voice libraries optimized for individual task recognition, while group bots have libraries optimized for group interaction patterns. This localized optimization improves speech recognition accuracy for each bot type without requiring all bots to use computationally intensive universal libraries, thus balancing accuracy with processing efficiency.
Data Source
AI summary
A method includes receiving, by a group messaging service, a message including recorded audio and a first group identifier, and determining that the group includes a bot. The method also includes determining whether the bot is a user bot responsive to a user node in the group or a group bot responsive to each of the one or more user nodes, selecting a bot voice library to process the recorded audio, sending, by the group messaging service, the recorded audio to the determined user bot or group bot, processing the recorded audio to produce enhanced text, performing, by the determined user bot or group bot, one or more designated actions corresponding to one of the recorded audio and the enhanced text, and sending, by the determined user bot or group bot, an audio reply to the group messaging service.