Adaptive Audio Attribute Tuning for Speaker Accent Intelligibility
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Solution Overview
Problem
Users face challenges in manually adjusting home-theater audio settings to suit their individual preferences and environment, which can be time-consuming and distracting, especially when switching between different content types or channels.
Innovation Solution
An audio adjustment system analyzes content characteristics such as accent, ethnic origin, gender, and user preferences to dynamically adjust audio attributes like volume, bass, and treble, and separates audio channels for optimal output across multiple devices, considering the user's location and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually adjust audio settings to suit individual preferences, then audio quality is improved, but user convenience deteriorates due to time-consuming adjustments
Solution Approach 1:
The system automatically analyzes content characteristics (accent, ethnic origin, gender) and user environment (acoustics, location) to adjust audio attributes without manual intervention. The audio processing system serves itself by making intelligent adjustments based on analyzed data, eliminating the need for users to manually configure settings while maintaining high audio quality
Solution Approach 2:
The system dynamically changes audio parameters (volume, treble, base control) based on analyzed content and environmental characteristics. By automatically adjusting these parameters according to the speaker's accent and the room's acoustics, the system achieves optimized audio quality without requiring user intervention
2Adaptability or versatility
If users frequently change channels and content types, then content variety is improved, but audio adjustment efficiency deteriorates due to repeated manual adjustments
Solution Approach 1:
The system performs preliminary analysis of content characteristics (accent, ethnic origin, gender) and user environment before audio playback begins. By pre-configuring optimal audio settings based on the content type and environmental factors, the system eliminates the need for repeated adjustments when users switch between different content
Solution Approach 2:
The system dynamically adjusts audio attributes in real-time based on changing content characteristics and environmental conditions. This dynamic adaptation allows the system to efficiently handle frequent channel changes and content type variations without requiring manual reconfiguration, maintaining high adjustment efficiency across diverse content
3Measurement precision
If audio attributes are dynamically adjusted based on content analysis, then user perception is improved, but system complexity increases
Solution Approach 1:
The system segments the audio processing task into distinct analysis components (content analysis for accent/ethnic origin/gender, environmental analysis for acoustics/location) and adjustment components. This segmentation allows complex processing to be organized into manageable modules, improving user perception through comprehensive analysis while managing system complexity through structured organization
Data Source
AI summary
Embodiments are directed towards analyzing content to adjust audio attributes of an audio component of the content to improve a user's audible perception of the content. The content is analyzed to determine an accent of an individual speaking in the content, an ethnic origin or gender of the individual, a genre of the content, or user preferences of the user, or some combination thereof. One or more of these determined characteristics is utilized to select and adjust at least one audio attribute of the audio component of the content, e.g., the volume, base, or treble. The audio component of the content is then output to at least one audio output device based on the at least one adjusted audio attribute. These audio attribute adjustments can improve a user's perception of the audio component, which can improve the user's understanding of the individual speaking in the content.