Digital Assistant Creation Using Natural Language Configuration
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Solution Overview
Problem
The creation of digital assistants is often complex and limited, with existing methods requiring programming skills or predetermined settings that do not allow for user flexibility and personalization.
Innovation Solution
A method and apparatus that allows users to create digital assistants using natural language input, enabling the configuration of settings such as response style, functions, workflows, and response formats, with the assistance of a model to determine responses based on the input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional methods are used to create digital assistants, then the assistants can have intelligent conversation and task processing capabilities, but the creation process becomes complex and limited, requiring programming skills or predetermined settings
Solution Approach 1:
The patent replaces traditional programming-based configuration methods with a natural language processing system. Users can create and configure digital assistants by typing or speaking natural language descriptions instead of writing code or navigating complex settings menus. The system automatically parses the natural language input and generates the corresponding digital assistant configuration, substituting the mechanical process of programming with an automated language understanding process.
Solution Approach 2:
The system enables users to self-configure digital assistants without requiring external assistance from developers or system administrators. By allowing users to directly describe their desired assistant behavior in natural language, the system empowers end-users to create customized assistants independently, eliminating the need for specialized technical knowledge or predetermined template selection.
2Adaptability or versatility
If programming skills are required to create digital assistants, then precise control over assistant behavior can be achieved, but user accessibility is limited to technically skilled individuals
Solution Approach 1:
The patent replaces the programming language interface with a natural language interface. Instead of requiring users to learn syntax, semantics, and logic of programming languages, the system accepts natural language descriptions and automatically translates them into functional digital assistant configurations. This substitution maintains precise control over assistant behavior while making the creation process accessible to all users regardless of technical background.
Solution Approach 2:
The system changes the fundamental parameter of user input from structured programming code to unstructured natural language. This parameter change allows the system to leverage advanced natural language processing and machine learning techniques to interpret user intent and generate appropriate digital assistant configurations, thereby expanding accessibility while maintaining versatility.
3Ease of operation
If predetermined settings are used for digital assistants, then the creation process is simplified, but user personalization and freedom in configuring assistant behavior is restricted
Solution Approach 1:
The patent transforms the static, predetermined settings into a dynamic configuration system. Instead of offering users a fixed set of pre-defined options, the system dynamically generates configuration parameters based on the user's natural language description. This allows the creation process to remain simple for users while enabling unlimited personalization, as the system adapts its output to match the specific needs described by each user.
Solution Approach 2:
The system performs preliminary analysis and interpretation of user intent through natural language processing before generating the digital assistant configuration. By pre-processing the user's natural language input to extract key requirements and constraints, the system can automatically generate highly personalized configurations without requiring users to manually adjust multiple settings, thus maintaining simplicity while achieving high adaptability.
Data Source
AI summary
A query-processing system processes an input audio stream that represents a succession of queries spoken by a user. The query-processing system listens continuously to the input audio stream, parses queries and takes appropriate actions in mid-stream. In some embodiments, the system processes queries in parallel, limited by serial constraints. In some embodiments, the system parses and executes queries while a previous query's execution is still in progress. To accommodate users who tend to speak slowly and express a thought in separate parts, the query-processing system halts the outputting of results corresponding to a previous query if it detects that a new speech utterance modifies the meaning of the previous query.