Audio Content Summarization via Point of Interest Detection
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Solution Overview
Problem
Current technologies face challenges in efficiently summarizing and reviewing audio content, particularly in identifying points of interest within oral conversations, which can lead to time-consuming processes when scanning through hours of recordings.
Innovation Solution
A system that identifies points of interest in audio content based on energy levels, speaker activity, and user-defined preferences, allowing for customized compilation and annotation of audio content, along with contextual information such as time and location, to facilitate efficient review and summarization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If audio content is recorded and stored for later review, then information preservation is improved, but review time increases significantly
Solution Approach 1:
The patent segments audio content by identifying and marking specific points of interest (POIs) within the recording. These POIs are determined based on energy levels, speaker activity, and other criteria. By dividing the continuous audio stream into meaningful segments anchored at POIs, the system enables selective review of only relevant portions rather than scanning entire hours of content.
Solution Approach 2:
The system performs preliminary analysis of audio content during or immediately after recording to identify and mark points of interest. This advance segmentation and tagging allows users to later navigate directly to marked POIs without manual scanning. The preliminary action of identifying POIs creates an index structure that accelerates subsequent review processes.
2Measurement precision
If manual review of recorded content is performed, then detailed analysis is improved, but productivity decreases
Solution Approach 1:
The patent introduces an intermediary system that automatically analyzes audio content and identifies points of interest based on multiple criteria including energy levels, speaker activity, and contextual factors. This intermediary POI identification layer bridges the gap between raw audio data and human review, providing structured markers that guide detailed analysis without requiring manual scanning of entire recordings.
3Loss of information
If comprehensive audio recording is captured, then information completeness is improved, but device complexity increases
Solution Approach 1:
The system employs self-service mechanisms where the audio recording device automatically performs analysis and identification of points of interest without requiring external intervention. The device uses built-in processors to analyze energy levels, detect speaker activity, and mark POIs autonomously during or after recording, reducing the complexity burden on users while maintaining comprehensive information capture.
Data Source
AI summary
Providing for summarization and analysis of audio content is described herein. By way of example, an oral conversation can be analyzed, such that points of interest within the oral conversation can be identified and file locations related to such points of interest can be marked. Points of interest can be inferred based on a level of energy, e.g., excitement, pitch, tone, pace, or the like, associated with one or more speakers. Alternatively, or in addition, speaker and/or reviewer activity can form the basis for identifying points of interest within the conversation. Moreover, a compilation of the identified points of interest and portions of the original oral conversation related thereto can be assembled. As described herein, audio content can be succinctly summarized with respect to inferred and/or indicated points of interest, to facilitate an efficient and pertinent review of such content.