Real-Time Audio Quality Scoring for Videoconferencing
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Solution Overview
Problem
Existing electronic devices lack real-time awareness of audio signal quality, leading to uncertainties about the presence of audio events like echoes, whispers, or background noises in transmitted audio signals during videoconferencing, which can disrupt user experiences.
Innovation Solution
An electronic device calculates a quality score for audio signals by assigning disruption scores to detected audio events and displaying them in real-time, allowing users to take corrective actions before transmission, using a processor coupled with an audio input device and display device to determine and display the quality score based on a running average of disruption scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If audio signals are transmitted during videoconferencing without quality monitoring, then transmission simplicity is maintained, but user awareness of audio quality deteriorates
Solution Approach 1:
The patent introduces an intermediary quality score indicator that mediates between the audio signal processing system and the user. This indicator serves as a communication bridge, translating complex audio quality metrics into simple visual cues (color-coded scores) that users can immediately understand without requiring complex monitoring systems or technical knowledge.
Solution Approach 2:
The system implements feedback by continuously monitoring audio signal quality and providing real-time quality scores to users. This feedback loop enables users to understand the current audio quality state and take corrective actions (such as adjusting microphones or closing applications) to improve the quality before transmission occurs.
2Reliability
If real-time audio quality monitoring is implemented, then user awareness of audio events is improved, but processing complexity increases
Solution Approach 1:
The patent segments the audio quality assessment into distinct components: detecting specific audio events (echoes, whispers, background noises), assigning disruption scores to each event type, and aggregating these into an overall quality score. This segmentation allows the system to handle complex processing tasks in manageable, modular steps rather than requiring a monolithic complex system.
Solution Approach 2:
The system changes parameters by transforming raw audio signal characteristics into standardized disruption scores and quality metrics. By defining specific parameters for different audio events (echo level, background noise threshold, whisper detection sensitivity), the system can reliably assess audio quality through consistent, measurable parameters rather than subjective evaluation.
3Manufacturing precision
If audio events are detected and processed, then audio quality is improved, but transmission time is increased
Solution Approach 1:
The system performs preliminary detection and assessment of audio events before the audio signal is transmitted. By identifying quality issues in advance and providing users with timely feedback, the system enables corrective actions to be taken before transmission, preventing poor quality audio from being sent in the first place rather than requiring extensive post-processing.
Solution Approach 2:
The patent implements efficient processing by skipping unnecessary analysis steps for clearly identifiable audio events. When specific audio events (such as loud background noises or strong echoes) are detected, the system can quickly assign disruption scores and generate quality indicators without performing exhaustive analysis, thus reducing processing time while maintaining quality assessment accuracy.
Data Source
AI summary
In some examples, a non-transitory machine-readable medium is provided. The non-transitory machine-readable medium stores machine-readable instructions that, when executed by a processor of an electronic device, cause the processor to receive an audio signal over a time period, to detect audio events in the audio signal, to assign a distinct disruption score to each of the audio events, to calculate a running average of the disruption scores, and to cause a display device to display a quality score based on the running average, where the quality score is indicative of a perceived quality of the audio signal.