Speech Extraction Workflow for Business Negotiation Reports
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Solution Overview
Problem
Existing information processing systems struggle to efficiently summarize and analyze communication sessions, such as business negotiations, by accurately extracting relevant information from speech data to generate insightful reports.
Innovation Solution
Utilizing a large-scale language model (LLM) to convert speech into text, identify extraction items and groups, and generate business negotiation and analysis reports by aggregating extraction results from multiple sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If speech data from communication sessions is manually analyzed and summarized, then relevant information can be extracted, but the process is time-consuming and inefficient
Solution Approach 1:
The patent replaces manual mechanical analysis with automated speech recognition and natural language processing systems. The circuitry automatically transcribes speech to text data and extracts relevant information without human intervention, dramatically improving productivity while reducing time loss.
2Loss of information
If all speech data from communication sessions is processed and stored, then complete information is available, but the data volume becomes unmanageably large
Solution Approach 1:
The patent extracts only the essential and relevant information from complete speech data using predefined extraction items. The circuitry identifies and extracts specific utterance information related to particular topics or keywords, retaining only necessary data while discarding redundant content, thus maintaining information quality without storing excessive data volume.
Solution Approach 2:
The patent segments the complete speech data into meaningful units based on extraction items and groups. The circuitry divides the continuous speech stream into discrete extractable elements organized by categories, making the data manageable and easier to process while preserving the essential information structure.
3Ease of operation
If generic summaries are generated from communication sessions, then overall content is captured, but specific insights and actionable information are lost
Solution Approach 1:
The patent applies different extraction criteria and analysis depths to different segments of the communication data based on local requirements. The circuitry identifies specific regions or topics within the speech data that require detailed extraction and applies targeted processing to those areas, ensuring that important specific insights are preserved while maintaining overall simplicity.
Data Source
AI summary
An information processing system includes circuitry that: acquires speech uttered by a first participant and a second participant, the first participant and the second participant participating in a communication session; acquires text data from the speech through speech recognition; receives a setting of an extraction item to be extracted from the text data; and acquires an extraction result obtained by extracting first utterance information related to the extraction item from the text data.