Crowdsourced Audio Normalization for Streaming Media
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Solution Overview
Problem
Conventional streaming video systems fail to provide an optimal audio experience for users due to default audio levels that may be too loud or too low, requiring constant volume adjustments, and do not account for individual user preferences or device-specific audio systems.
Innovation Solution
A system that allows users to select an automatic audio adjustment feature, which analyzes historical volume adjustments and user profiles to determine a recommended volume level for each segment of media content, dynamically normalizing audio levels based on user behavior and device capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If default audio levels are used for streaming video, then the audio content can be delivered without additional processing, but the audio may be too loud or too low requiring constant volume adjustments by users
Solution Approach 1:
The system performs preliminary analysis of audio content to determine optimal volume levels for different segments before playback. Volume normalization data is pre-calculated and stored, allowing the device to automatically adjust volume without requiring real-time processing or user intervention during playback.
Solution Approach 2:
The audio system automatically adjusts volume levels based on pre-analyzed content characteristics and user preferences. The system serves itself by making autonomous volume decisions without requiring user operation, thereby reducing the frequency of manual volume adjustments.
2Reliability
If constant volume adjustments are implemented to optimize audio experience, then audio quality improves, but user convenience deteriorates due to frequent interactions
Solution Approach 1:
The system incorporates user feedback regarding volume preferences to continuously refine and personalize volume adjustment strategies. By learning from user behavior patterns, the system anticipates user needs and makes proactive volume adjustments that maintain audio quality consistency without requiring explicit user interactions.
Solution Approach 2:
The system autonomously manages volume adjustments based on pre-analyzed audio segments and learned user preferences, eliminating the need for frequent manual volume changes while maintaining consistent audio quality throughout playback.
3Loss of energy
If audio content is delivered without normalization, then bandwidth usage is minimized, but user experience deteriorates due to inappropriate volume levels for different devices and locations
Solution Approach 1:
The system applies different volume normalization characteristics to different segments of audio content based on their specific characteristics. Rather than uniformly processing all audio, the system tailors normalization parameters to local segments, optimizing for both bandwidth efficiency and device compatibility.
Solution Approach 2:
The system dynamically adjusts audio parameters including volume levels based on device capabilities and playback context. By changing parameters adaptively rather than applying fixed normalization, the system achieves broad device compatibility while minimizing unnecessary data transmission.
4Adaptability or versatility
If personalized audio profiles are implemented, then user experience is enhanced, but system complexity increases due to data collection and processing requirements
Solution Approach 1:
The system collects and processes user preference data in advance to build personalized audio profiles before actual playback occurs. This preliminary profiling enables the system to make instant, context-aware volume adjustments without requiring complex real-time processing during playback.
Data Source
AI summary
Various embodiments provide methods and systems for providing a recommended volume level in presentation of media content. In some embodiments, volume adjustment events made by a user and/or similar users while watching media content can be detected and automatically recorded. The media content may include a plurality of segments. A normalized volume level for at least one segment of the media content can be determined by aggregating the recorded volume adjustment events corresponding to the at least one segment of the media content. When the media content is played back on a user device, at least some embodiments cause the at least one segment of the media content to be played back at a recommended volume level determined based at least in part upon one of the normalized audio level of the corresponding segment, the audio system of the user device, or historical data and personal profile of the user.