Audio Playback Volume Adjustment Through Structured LLM Context Detection
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Solution Overview
Problem
Existing client devices often auto-play audio content at high volumes without user input, leading to undesirable noise levels in certain environments or scenarios, such as libraries or places of worship, where users may not have time to adjust the volume before playback begins.
Innovation Solution
Utilizing a structured large language model (LLM) to determine the context of the client device or user and adjust audio playback settings, such as reducing volume automatically based on predefined contexts, including location, ambient noise, and time, allowing for smart and flexible customization of playback settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If audio content is auto-played at high volume, then the user experience is improved through immediate audio rendering, but noise disturbances occur in inappropriate environments such as libraries or places of worship
Solution Approach 1:
The system performs preliminary context assessment before audio playback by analyzing contextual signals (location, ambient noise, time) and determining whether the environment is appropriate for high-volume playback. This preliminary action prevents noise disturbances before they occur by adjusting playback volume in advance based on the assessed context.
Solution Approach 2:
The audio playback volume is made dynamic rather than static. The system continuously monitors contextual signals and adjusts the playback volume accordingly - high volume in appropriate environments (personal spaces, noisy environments) and low volume in inappropriate environments (libraries, places of worship). This dynamic adjustment resolves the contradiction by making volume adaptive to context.
2Ease of operation
If the client device automatically begins rendering audio content without user input, then convenience is improved, but the user loses control over playback volume and timing
Solution Approach 1:
The system provides self-service by automatically assessing context and adjusting playback parameters without requiring explicit user input for each decision. The device monitors contextual signals and autonomously determines appropriate playback volume and timing, maintaining convenience while adapting to environmental conditions.
Solution Approach 2:
The system implements feedback loops by continuously monitoring contextual signals (location, ambient noise level, time) and using this information to adjust playback behavior. This feedback mechanism allows the system to maintain automatic convenience while adapting to user needs and environmental conditions, effectively providing control without requiring direct user intervention.
3Productivity
If the user is provided with insufficient time to prevent high-volume playback, then automatic playback efficiency is maintained, but the user cannot adjust settings before playback begins
Solution Approach 1:
The system performs preliminary context assessment and volume determination before audio playback begins. By analyzing contextual signals in advance and pre-determining the appropriate playback volume, the system eliminates the need for user adjustment during playback initiation, maintaining both speed and user needs.
Solution Approach 2:
The system dynamically adjusts playback parameters based on real-time context assessment before playback begins. This dynamic pre-adjustment allows the system to maintain fast playback initiation while adapting volume to environmental conditions, effectively providing user-preferred settings without requiring explicit user input or adjustment time.
Data Source
AI summary
Implementations relate to modifying one or more audio content playback settings of a client device. Processor(s) can receive one or more contextual signals associated with the client device or a user of the client device and can generate, based on at least the one or more contextual signals and a predefined context, a structured large language model (LLM) query. The processor(s) can generate, based on processing the structured LLM query, an LLM output that includes at least an indication of whether the client device or the user is in the predefined context. The processor(s) can determine, based on processing the indication, whether the client device or the user device is in the predefined context and, responsive to determining that the client device or the user is in the predefined context, modify one or more audio content playback settings of the client device for rendering audio content.