Communication Data Log Processing Apparatus
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Solution Overview
Problem
Communication data logs from IoT applications, such as field services and conferences, are difficult to structure due to changing subjects, parallel subjects, and the inclusion of both spoken and written language, making it challenging to analyze and utilize effectively for improving services.
Innovation Solution
A communication data log processing apparatus that receives and structures communication data by determining sections based on speech sentences and meta information, using a processor with a relevance evaluation model to classify data into relevant sections, and considering speech intervals and meta data for accurate grouping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If communication data is structured by dividing into sections of the same subject, then analysis effectiveness is improved, but the complexity of structuring increases due to changing subjects and parallel conversations
Solution Approach 1:
The communication data log is segmented into multiple sections based on speech intervals and subject changes. The processor divides the continuous communication data into discrete sections where each section contains speeches related to a specific subject, making analysis more effective while managing complexity through systematic segmentation.
Solution Approach 2:
Meta information acts as an intermediary element that bridges speech content and section classification. The processor uses meta information (such as speech intervals, speaker identifiers, and contextual data) as a mediator to automatically determine section boundaries and group related speeches, reducing the complexity of manual structuring.
2Measurement precision
If speech intervals and meta information are considered for section determination, then sectioning accuracy is improved, but processing time increases
Solution Approach 1:
Meta information is extracted and prepared in advance before section determination. The processor pre-processes speech intervals, speaker identifiers, and other contextual data into structured formats, enabling faster and more accurate section determination without increasing real-time processing time.
Solution Approach 2:
The processor transforms raw communication data into standardized parameters including speech interval durations, speaker turn counts, and subject transition markers. By changing the data representation into comparable parameters, the system achieves accurate sectioning while maintaining efficient processing through parameter-based comparison rather than full content analysis.
Data Source
AI summary
According to one embodiment, a communication data log processing apparatus includes a processor including hardware. The processor receives communication data contained in a communication data log as a log of the communication data containing a speech sentence and meta information. The processor determines a section to which the received communication data should belong based on the speech sentence and the meta information.