Audio-Driven Text Document Updating via Topic Segmentation
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Solution Overview
Problem
Manual updating of lengthy text documents based on oral proceedings is time-consuming and prone to errors, with no effective method to incorporate changes from audio recordings into the documents.
Innovation Solution
A method that segments text documents into topic-based segments, converts audio recordings to text, matches and updates relevant segments based on novelty criteria, and automatically incorporates new content into the text documents to modify device operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updating of text documents based on oral proceedings is performed, then the document can be updated with changes from audio recordings, but the process is time-consuming and prone to errors
Solution Approach 1:
The patent replaces the manual mechanical process of updating documents with an automated computer-based system. The system automatically converts audio recordings to text, segments both the document and audio text into topics, matches corresponding segments, and updates the document without human intervention, thereby eliminating time consumption and human error while maintaining high accuracy through systematic processing
Solution Approach 2:
The system performs self-service by automatically completing the entire document updating process. It independently converts audio to text, segments content by topic, identifies matches between document and audio segments, determines novelty, and updates the document autonomously, freeing users from manual updating tasks while ensuring consistent and accurate results
2Measurement precision
If the text document is segmented into topic-based segments and audio is converted to text and segmented, then relevant segments can be accurately matched and updated, but the processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing both the text document and converted audio text into distinct topic-based segments. This allows precise matching of corresponding segments while managing complexity through modular processing - each segment is independently analyzed and matched based on its specific topic, improving precision without overwhelming system complexity
Solution Approach 2:
The system changes the parameter of text organization from unstructured or simple structured format to topic-based segmented format. This parameter change enables precise matching by creating a structured framework where segments can be systematically compared and matched based on their topic parameters, enhancing precision while the automated system manages the processing complexity
3Loss of information
If novelty criteria are applied to identify differences between text segments and audio segments, then only relevant new content is incorporated, but the processing time increases
Solution Approach 1:
The system performs preliminary action by pre-segmenting both the document and audio text into topics before comparison. This preliminary organization allows the novelty assessment to focus only on matching corresponding segments rather than analyzing entire texts, significantly reducing the time required for novelty detection while ensuring all novel information is captured through systematic comparison
4Productivity
If automatic updating of text documents from audio recordings is implemented, then efficiency is improved and errors are reduced, but the system complexity increases
Solution Approach 1:
The patent applies universality by designing a multi-functional automated system that performs multiple tasks: audio-to-text conversion, text segmentation, topic matching, novelty detection, and document updating. This single integrated system handles the entire document updating process, improving productivity significantly while managing system complexity through consolidated multi-functionality rather than separate independent systems
Data Source
AI summary
A method modifies and utilizes a text document based on an audio file that has captured audio proceedings relevant to the text document. One or more processors and/or a user segment the text document into topic-based text segments. Processor(s) receive an audio file that is relevant to the text document, convert the audio file into text, and match a specific topic-based text segment from the topic-based text segments to a specific topic-based audio segment from the topic-based audio segments. In response to identifying a difference between content in the specific topic-based text segment and content in the specific topic-based audio segment, processor(s) and/or the user update the specific topic-based text segment with the content in the specific topic-based audio segment to create an updated version of the text document.