3D Audio Re-spatialization from Legacy 2D Video
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Solution Overview
Problem
Legacy audiovisual media lacks full audio spatialization, resulting in a loss of spatial information when recorded in environments with reflective surfaces, as the direct and reflected sounds are mixed into mono or stereo formats, leading to a non-immersive listening experience.
Innovation Solution
A method to convert two-dimensional audio from legacy video into three-dimensional audio by isolating individual sound sources using source separation techniques, removing reverberation, and re-spatializing the direct sound components based on acoustic characteristics of the local area, using visual and audio features, and a mapping server to generate a local area impulse response for immersive audio presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If 2-D audio from legacy video is converted to 3-D audio using source separation and re-spatialization, then spatial awareness and immersion are enhanced, but device complexity and processing requirements increase
Solution Approach 1:
The audio signal is segmented into individual sound sources using source separation techniques. Each sound source is processed independently to extract spatial characteristics and apply appropriate 3-D audio rendering, thereby recovering spatial information that was lost in the original 2-D mixing while managing complexity through modular processing of separate sources.
Solution Approach 2:
An audio processing system acts as an intermediary between legacy 2-D audio content and the 3-D audio output. This intermediary performs source separation, spatial analysis, and re-spatialization operations, bridging the gap between simple 2-D recordings and immersive 3-D audio experiences without requiring changes to the original content or playback devices.
2Measurement precision
If reverberation is removed to obtain direct sound components, then spatial accuracy is improved, but processing complexity increases
Solution Approach 1:
Reverberation components are extracted and removed from the audio signal to isolate direct sound components. This extraction process separates the useful direct sound information from the distracting reverberant energy, improving spatial accuracy by focusing on the direct path sound while eliminating the complex reflected sound fields that obscure spatial cues.
3Reliability
If local area impulse response is generated using visual and audio features, then audio realism is improved, but processing time and computational resources increase
Solution Approach 1:
Acoustic characteristics of the local area are determined in advance by analyzing visual features of the environment and audio reverberation properties. This preliminary analysis creates a model of the acoustic space that can be reused for multiple sound sources, reducing processing time while maintaining audio realism through pre-computed spatial and acoustic parameters.
Solution Approach 2:
The local area impulse response generation process serves multiple functions: it analyzes visual features of the environment, characterizes acoustic properties from audio reverberation, and creates a reusable acoustic model. This multi-functional approach consolidates processing efforts, reducing overall computational requirements and processing time while improving audio realism through comprehensive environmental characterization.
Data Source
AI summary
An audio system generates virtual acoustic environments with three-dimensional (3-D) sound from legacy video with two-dimensional (2-D) sound. The system relocates sound sources within the video from 2-D to into a 3-D geometry to create an immersive 3-D virtual scene of the video that can be viewed using a headset. Accordingly, an audio processing system obtains a video that includes flat mono or stereo audio being generated by one or more sources in the video. The system isolates the audio from each source by segmenting the individual audio sources. Reverberation is removed from the audio from each source to obtain each source's direct sound component. The direct sound component is then re-spatialized to the 3-D local area of the video to generate the 3-D audio based on acoustic characteristics obtained for the local area in the video.