Audio Content Augmentation for Missing and Imbalanced Context Sounds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Audio content in multimedia items, such as movies or television shows, may have portions that are too loud, too low, or missing, negatively impacting user experience, especially for visually impaired individuals who rely heavily on audio for context.
Innovation Solution
Analyze visual and textual content to identify candidate auditory events that should be included or enhanced in the audio content, using deep neural networks to correlate media elements with an auditory event repository, and modify the audio content accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audio content is left unchanged, then the original audio quality is preserved, but visually impaired users cannot adequately perceive contextual sounds
Solution Approach 1:
The system performs preliminary analysis of visual content and existing audio content before generating augmentation decisions. Visual content is analyzed to identify contextual sounds that should be present, and this analysis is done in advance to guide the audio augmentation process, ensuring that visually impaired users receive appropriate contextual audio information.
Solution Approach 2:
The system introduces an intermediary processing layer that bridges visual content and audio content. This intermediary system analyzes visual scenes, compares them with existing audio, and generates appropriate audio augmentations, acting as a mediator between the visual and audio modalities to improve context perception for visually impaired users.
2Loss of information
If audio content is augmented with additional sounds, then context perception is improved, but the audio content becomes more complex and may include inappropriate sounds
Solution Approach 1:
The system employs feedback mechanisms where the analyzed visual content and existing audio content are continuously compared against the augmented audio output. This feedback loop ensures that only contextually appropriate sounds are added, and the system can adjust the augmentation based on the perceived effectiveness, preventing inappropriate sounds from being included.
Solution Approach 2:
The audio augmentation is applied locally and specifically to match the visual context being depicted. Rather than adding generic sounds, the system identifies the specific contextual sounds needed for each visual scene and augments only those particular audio elements, maintaining precision and avoiding unnecessary complexity.
3Manufacturing precision
If existing audio is amplified, then audibility is improved, but loudness balance is disrupted and other sounds become less perceptible
Solution Approach 1:
The system dynamically changes audio parameters including volume, frequency, and timing of augmented sounds. Rather than simply amplifying existing audio, the system adjusts multiple parameters to integrate augmented sounds harmoniously with the original audio track, maintaining overall loudness balance while improving the perception of contextual sounds.
Data Source
AI summary
The audio content (e.g., an audio track, an audio file, an audio signal, etc.) of a content item (e.g., multimedia content, a movie, streaming content, etc.) may be modified to augment and/or include one or more auditory events, such as a sound, a plurality of sounds, a sound effect(s), a voice(s), and/or music.