Synthetic Audio Generation from Video Visual Features
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Solution Overview
Problem
Video content often lacks synchronized audio, particularly when recorded without proper microphones, leading to missing or distorted sound, which affects user experience and immersion in media consumption.
Innovation Solution
A computing device and method that extract visual features from video segments to generate a synthetic audio stream, using a generator network trained with historical data to create a predicted spectrogram and synchronize it with the video feed, emphasizing dominant features and de-emphasizing non-dominant ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If video content is recorded without proper microphones, then device complexity is reduced, but audio quality and synchronization are lost
Solution Approach 1:
The patent introduces an intermediary system consisting of visual feature extraction, spectrogram generation, and audio synthesis components that mediate between the video content and the final audio output. This intermediary process converts visual information into corresponding audio representations, resolving the contradiction by adding audio capability without requiring traditional microphones or complex recording hardware.
2Ease of operation
If audio is added to video content, then user experience is improved, but synchronization accuracy may deteriorate
Solution Approach 1:
The patent applies preliminary action by extracting visual features and generating spectrograms from video frames before synthesizing the final audio waveform. This sequential preprocessing ensures that the audio is generated based on the actual visual content at each moment, maintaining temporal alignment and synchronization between audio and video while enhancing user experience.
3Measurement precision
If visual features are extracted and processed for each video segment, then audio accuracy is improved, but processing time increases
Solution Approach 1:
The patent divides the video content into discrete segments or frames, extracting visual features independently for each segment. This segmentation allows for parallel processing of multiple video frames, improving audio accuracy by capturing temporal variations while enabling efficient computation that reduces overall processing time through distributed calculation.
Data Source
AI summary
A computing device receives a video feed. The video feed is divided into a sequence of video segments. For each video segment, visual features of the video segment are extracted. A predicted spectrogram is generated based on the extracted visual features. A synthetic audio waveform is generated from the predicted spectrogram. All synthetic audio waveforms of the video feed are concatenated to generate a synthetic soundtrack that is synchronized with the video feed.