Audio Playback Context Navigation via NLP Transition Points
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Solution Overview
Problem
Current audio playback systems are inefficient for quickly locating specific portions of interest in recordings, such as voicemails or conferences, due to static fast-forward functionality, making it time-consuming to find desired content.
Innovation Solution
Implementing a method that uses natural language processing to transcribe and annotate audio recordings, identifying transition points based on context changes, and presenting a playback interface with graphical and textual indicators to allow users to fast-forward to specific points or follow their profile-defined interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If static fast-forward function is used, then device complexity is reduced, but time to locate desired content increases
Solution Approach 1:
The system performs preliminary analysis of the audio recording before playback to identify transition points and generate a transcript with contextual markers. This advance preparation creates a roadmap that enables rapid navigation during playback without requiring complex real-time processing when the user needs to locate specific content.
Solution Approach 2:
The patent introduces an intermediary layer between the user and the audio content in the form of a transcript with highlighted contextual portions and transition points. This intermediary structure allows users to quickly scan and identify relevant sections without directly searching through the entire audio recording, thereby reducing time loss while maintaining manageable system complexity.
2Ease of operation
If natural language processing and context analysis are implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The audio recording is segmented into multiple portions based on transition points identified through natural language processing. Each segment represents a distinct contextual unit (e.g., different topics, speakers, or conversational turns). This segmentation allows the system to provide targeted navigation to specific portions without requiring the entire system to be overly complex, as each segment can be independently analyzed and referenced.
Solution Approach 2:
The system applies natural language processing and context analysis selectively to identify meaningful transition points and annotate specific portions of the transcript, rather than uniformly processing every segment with equal complexity. This local quality approach enhances ease of operation at key navigation points while avoiding unnecessary complexity in less critical areas.
3Productivity
If dynamic fast-forward based on profile is implemented, then productivity is improved, but loss of information increases
Solution Approach 1:
The system incorporates user profiles that provide feedback about user preferences and interests. This feedback mechanism allows the dynamic fast-forward function to adapt to individual users, skipping portions they are less likely to find interesting while preserving sections aligned with their profile. This maintains productivity by efficiently directing users to relevant content while minimizing information loss through profile-based personalization.
Solution Approach 2:
The system changes parameters such as fast-forward speed and section selection based on the user's profile and the identified context of each portion. By dynamically adjusting these parameters according to contextual relevance and user preferences, the system improves productivity by focusing on high-value content while preserving essential context information that matches user interests.
Data Source
AI summary
Embodiments are directed to controlling playback of recordings. The recording can comprise an audio recording, audio/visual recording, voicemail message, or other recording having an audio component. According to one embodiment, a method can comprise capturing an audio recording of speech of at least one person and determining, a context for each of a plurality of portions of the audio recording based on natural language processing of the audio recording. One or more transition points between the portions of the audio recording can be identified. Each transition point can indicate a change in the determined context between the portions. A playback interface providing a representation of the audio recording and each of the identified transition points can be presented and the audio recording can be played based on input received through the playback interface.