Dynamic Audio Adaptation in Extended Reality
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies for playing back audio-visual content lack the ability to dynamically adjust audio based on user context and interaction in extended reality environments, failing to enhance the playback experience by aligning audio with user actions and spatial positioning.
Innovation Solution
The system determines context based on user actions and spatial positioning within an extended reality environment, selecting and synchronizing appropriate audio portions with visual content, using metadata and machine learning to provide enhanced audio experiences such as spatialized sound and ambient noise, transitioning between audio loops based on user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If audio playback is static and uniform for all users, then device complexity is reduced, but user engagement and immersion deteriorate
Solution Approach 1:
The audio playback system transitions from static to dynamic by continuously adjusting audio characteristics based on real-time user context. The system monitors user actions, spatial positioning, and interaction states to dynamically select and mix audio portions, creating an adaptive audio experience that evolves with user engagement.
Solution Approach 2:
The audio content is divided into multiple distinct audio portions (e.g., ambient noise, foreground sounds, spatialized audio streams) that can be independently selected and mixed. This segmentation allows the system to compose different audio configurations based on context without requiring complete reprocessing of the entire audio track.
2Reliability
If multiple audio portions are selected and mixed based on context, then immersion and realism are improved, but processing time and computational resources increase
Solution Approach 1:
Audio portions are pre-processed and organized into categories (ambient, foreground, spatialized streams) during content creation. Metadata is pre-generated to identify audio sources and types, enabling rapid selection and mixing during playback without requiring complex real-time analysis.
Solution Approach 2:
The system adjusts audio playback by changing parameters such as volume levels, spatial positioning, and selection of specific audio portions based on context. These parameter adjustments are computationally efficient compared to complete audio reprocessing, allowing quick adaptation to changing user states.
3Adaptability or versatility
If audio is continuously adjusted based on user context, then user engagement is improved, but energy consumption increases
Solution Approach 1:
Instead of continuous real-time adjustment, the system periodically updates audio configuration based on detected changes in user context. Audio portions are selected and mixed at discrete intervals triggered by user actions or state changes, reducing computational load while maintaining responsive behavior.
4Reliability
If spatialized audio and ambient noise are provided, then immersion is improved, but device complexity increases
Solution Approach 1:
The system uses metadata as an intermediary layer between the audio content and playback system. Metadata identifies audio sources, types, and spatial characteristics, enabling the playback system to automatically select and configure appropriate audio portions without requiring complex manual configuration or analysis of the audio signals themselves.
Data Source
AI summary
Various implementations disclosed herein include devices, systems, and methods that that modify audio of played back AV content based on context in accordance with some implementations. In some implementations audio-visual content of a physical environment is obtained, and the audio-visual content includes visual content and audio content that includes a plurality of audio portions corresponding to the visual content. In some implementations, a context for presenting the audio-visual content is determined, and a temporal relationship between one or more audio portions of the plurality of audio portions and the visual content is determined based on the context. Then, synthesized audio-visual content is presented based on the temporal relationship.


