Intelligent Audio Playback Resumption Using Context-Aware Rewind
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Solution Overview
Problem
Audio playback systems struggle to restore context effectively after longer pauses, as existing methods often resume playback with only a repetition of the last few seconds, which is insufficient for listeners to recall the context of audio content such as music, podcasts, or audiobooks.
Innovation Solution
An intelligent audio playback resumption method that determines the appropriate rewind length based on context complexity and interruption duration, using timestamp storage and analysis to adjust resumption settings through user feedback and reinforced learning, allowing playback to resume at the start of a sentence, section, or chapter for audiobooks, and at the paused position for music.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If playback resumes with repetition of the last few seconds, then the system maintains simplicity in resumption logic, but the listener cannot recall context after longer pauses
Solution Approach 1:
The system dynamically adjusts the resumption behavior based on the pause duration. For short pauses, it uses simple repetition of the last few seconds. For longer pauses, it automatically identifies and rewinds to appropriate contextual boundaries such as sentence endings, section breaks, or chapter markers, thereby adapting the resumption strategy to the specific situation while maintaining ease of operation.
Solution Approach 2:
The system changes the resumption parameter (rewind duration and target point) based on the pause length. Instead of using a fixed rewind duration, it adjusts the rewind amount dynamically - using small rewind amounts for short pauses and larger rewind amounts targeting structural boundaries for longer pauses, thus resolving the contradiction between simplicity and context preservation.
2Loss of information
If the system rewinds to contextual boundaries for longer pauses, then context recall is improved, but the resumption logic becomes more complex
Solution Approach 1:
The system performs preliminary analysis during the pause period to identify contextual boundaries (sentence endings, section breaks, chapter markers) before resumption is needed. By pre-identifying these boundaries and storing them, the actual resumption operation becomes simpler - it only needs to select from pre-computed options based on pause duration, rather than performing complex analysis at the moment of resumption.
Solution Approach 2:
The system automatically identifies contextual boundaries and determines appropriate rewind points without requiring user intervention. It serves itself by analyzing the audio content structure, storing boundary information, and autonomously selecting the optimal resumption point based on pause length, thereby managing the complexity internally while presenting a simple interface to the user.
3Device complexity
If the system uses fixed rewind duration, then the resumption mechanism is simple, but it cannot adapt to individual listener memory performance
Solution Approach 1:
The system incorporates feedback mechanisms to learn individual listener preferences and memory characteristics. By monitoring user interactions with the resumption feature (such as whether users rewind further or fast-forward after resumption), the system adapts the rewind duration and boundary selection to match individual listener needs, transitioning from a fixed to an adaptive resumption mechanism while managing complexity through iterative learning.
Data Source
AI summary
The present disclosure pertains to audio playback resumption and adjustment of audio resumption settings based on feedback. A first date timestamp and a playback timestamp of audio content may be stored when pausing audio content. Then when resuming the audio content, a time interval between the first date timestamp and a current date timestamp may be determined. A resumption timestamp in the audio content may be determined based on the time interval being within a certain time range. After resuming playback, a feedback input may be determined. The feedback may be used in adjusting the resumption settings. The adjusted resumption settings may be used in subsequent resumption of the same or different content.