Contextual Audio Generation for Digital Images
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Solution Overview
Problem
Existing methods fail to generate holistic audio for digital still images, as they either don't synthesize audio or produce static audio that doesn't dynamically reflect the image's context, missing the immersive experience of capturing the audio at the time and location of the image.
Innovation Solution
A method and system that analyze key image features and contextual data to determine scene-themes and viewer themes, generating contextual audio by matching scene-objects and contextual data in real-time, using a processor to identify relevant audio files and assign contribution weightages for dynamic audio correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video is used to capture both visual and audio, then audio experience is improved, but storage space consumption increases
Solution Approach 1:
The patent separates audio and visual information into independent components. Instead of storing complete video files, it extracts and stores only audio features separately, reducing storage requirements while preserving audio experience when images are viewed
Solution Approach 2:
The patent creates simplified audio representations (audio features and embeddings) that are lightweight copies of the original audio information, allowing audio to be associated with images without storing full video files
2Loss of information
If existing audio extraction techniques are used, then individual object audio is obtained, but holistic audio experience is lost
Solution Approach 1:
The patent merges multiple individual object audios into a single holistic audio representation for the entire scene. By combining audio features from multiple detected objects and weighting them according to their importance, it recreates the overall audio environment rather than playing isolated sounds
Solution Approach 2:
The patent transforms individual object audio features into a weighted composite audio representation by adjusting parameters such as contribution weights based on object importance, distance, and scene context, thereby creating a natural-sounding holistic audio experience
3Ease of manufacture
If static audio is assigned to images, then implementation simplicity is maintained, but dynamic audio context is lost
Solution Approach 1:
The patent implements dynamic audio generation by computing audio representations in real-time based on current image content and context. Instead of using fixed pre-assigned audio, the system dynamically determines which objects are present and what audio they should produce based on the specific image being viewed
Solution Approach 2:
The patent changes audio parameters dynamically by adjusting contribution weights, audio selection, and mixing based on scene context, object importance, and viewer position, allowing the same image to produce different audio experiences based on contextual factors
4Loss of information
If comprehensive audio synthesis is implemented, then audio realism is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary processing by pre-computing audio features and embeddings during image capture or preprocessing stages. These pre-computed features are stored and can be quickly retrieved and combined during playback, reducing real-time computational requirements
Solution Approach 2:
The patent introduces audio embeddings and feature vectors as intermediary representations between raw audio and final audio output. These intermediaries simplify the complexity by providing a standardized format for combining and processing audio from multiple sources
Data Source
AI summary
Disclosed subject matter relates to digital media including a method and system for generating a contextual audio related to an image. An audio generating system may determine scene-theme and viewer theme of scene in the image. Further, audio files matching scene-objects and the contextual data may be retrieved in real-time and relevant audio files from audio files may be identified based on relationship between scene-theme, scene-objects, viewer theme, contextual data and metadata of audio files. A contribution weightage may be assigned to the relevant and substitute audio files based on contextual data and may be correlated based on contribution weightage, thereby generating the contextual audio related to the image. The present disclosure provides a feature wherein the contextual audio generated for an image may provide a holistic audio effect in accordance with context of the image, thus recreating the audio that might have been present when the image was captured.