Natural Language Output Profiles for Context-Aware Speech Personalization
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Solution Overview
Problem
Existing spoken language understanding systems lack the ability to generate natural language outputs using diverse speech/personality profiles, limiting user engagement and experience.
Innovation Solution
A system that determines and applies specific language generation profiles based on user preferences, device profiles, location, and content of user inputs to generate natural language outputs with varied attributes such as prosody, word insertion/replacement, and sentence structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single fixed speech style is used for natural language output, then system simplicity is maintained, but user engagement and experience are limited
Solution Approach 1:
The system dynamically selects speech profiles based on user preferences, device profiles, location, and input content rather than using a fixed speech style. This allows the system to adapt its speech characteristics in real-time, resolving the contradiction between maintaining simplicity and providing diverse speech styles.
Solution Approach 2:
The system changes speech parameters (prosody, word insertion, replacement, sentence structure) based on different contexts and user preferences. By modifying these linguistic parameters dynamically, the system achieves speech style diversity without fundamentally changing its core architecture.
2Adaptability or versatility
If multiple language generation profiles are implemented, then user engagement and experience are enhanced, but system complexity increases
Solution Approach 1:
The speech generation system is segmented into multiple language generation profiles, each with distinct characteristics. This segmentation allows the system to offer diverse speech styles while managing complexity by organizing profiles into discrete, selectable units rather than attempting to generate variations continuously.
Solution Approach 2:
Multiple language generation profiles are implemented within a single system framework that handles them universally. The system can switch between different profiles (e.g., formal, casual, enthusiastic) based on context, providing personalized experiences without requiring separate systems for each profile type.
3Adaptability or versatility
If speech profiles are customized based on user preferences and context, then interaction quality improves, but processing requirements increase
Solution Approach 1:
User preferences and device profiles are predetermined and stored in advance. When generating speech output, the system retrieves pre-configured profile information rather than creating it in real-time, reducing processing energy requirements while maintaining context-aware responsiveness.
Data Source
AI summary
A system is provided for determining a natural language output, responsive to a user input, using different speech personality profiles. The system may determine to user a particular language generation profile based at least in part on data relating to the user input and data corresponding to the response to the user input. The language generation profile may include different attributes that are used to determine the natural language output, such as, prosody, replacement words, injected words, sentence structure, etc.