Video Stream Quality Adaptation via Speech Detection
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Solution Overview
Problem
Video conferencing experiences can be negatively impacted by low-bandwidth or high-latency network connections, leading to poor video and audio quality, and disabling video may not be desirable as it affects other attendees.
Innovation Solution
A method that modifies video streams based on whether a user is speaking or not, reducing resource consumption by downgrading video quality when the user is not speaking, and adaptively adjusting based on network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video stream is transmitted at high quality, then video conferencing quality is improved, but network bandwidth consumption increases
Solution Approach 1:
The video stream quality is dynamically adjusted based on whether the user is speaking or not. When the user is not speaking, the video quality is downgraded to consume less bandwidth. This dynamic adjustment resolves the contradiction by making video quality adaptive rather than static, allowing high quality only when necessary (during speech) and reducing quality when unnecessary (during non-speech periods).
Solution Approach 2:
The patent changes the video stream parameters (quality, resolution, bitrate) based on speech detection results. When speech is detected, high-quality parameters are used; when no speech is detected, lower-quality parameters are applied. This parameter change strategy resolves the contradiction by optimizing the trade-off between video quality and bandwidth consumption in real-time.
2Loss of energy
If video stream quality is reduced to save bandwidth, then bandwidth consumption is reduced, but video conferencing quality deteriorates
Solution Approach 1:
Rather than continuously reducing video quality, the system dynamically adjusts quality based on speech detection. Video quality is maintained at high levels during speech segments (when it matters most for communication) and reduced during non-speech segments. This dynamic approach ensures quality is preserved when needed while saving bandwidth when not needed.
Solution Approach 2:
The system changes video stream parameters adaptively based on speech activity. High-quality parameters are applied during speech, and lower-quality parameters are applied during non-speech periods. This selective parameter change resolves the contradiction by ensuring quality degradation only occurs when it does not impact communication effectiveness.
3Manufacturing precision
If video is disabled to improve audio quality, then audio stream quality is improved, but other attendees cannot view the user
Solution Approach 1:
Instead of disabling video entirely, the system dynamically adjusts video quality based on speech detection and network conditions. This allows video to remain enabled and visible to attendees while adjusting quality to conserve bandwidth, resolving the contradiction between maintaining video visibility and optimizing resource usage.
Solution Approach 2:
The patent applies different quality levels to different parts of the video stream or different video streams sent to different attendees based on their network conditions. This allows the system to maintain adequate video quality for visibility while optimizing bandwidth consumption, rather than using a single uniform quality level for all attendees.
4Manufacturing precision
If video stream is continuously transmitted at high quality, then video conferencing quality is maintained, but network resources are wasted during non-speech periods
Solution Approach 1:
The system periodically detects speech activity and adjusts video quality accordingly. During speech periods, high-quality video is transmitted; during non-speech periods, quality is reduced. This periodic adjustment based on speech detection eliminates waste of network resources during non-speech periods while maintaining quality during speech periods, resolving the contradiction between continuous high quality and resource efficiency.
Solution Approach 2:
The video streaming system automatically adjusts its own quality based on speech detection feedback, without requiring manual intervention. The system serves itself by detecting when high quality is needed (during speech) and when it can be reduced (during non-speech), optimizing resource usage while maintaining quality standards automatically.
Data Source
AI summary
In one aspect, an example methodology implementing the disclosed techniques can include, by a computing device, receiving a video stream from a first client device and, responsive to a determination that a second client device activated a downgrade feature and further responsive to a determination that a user of the first client device is not speaking, modifying the video stream to consume less resources. The method can also include, by the computing device, providing the modified video stream to the second client device.