Communication Transcript Analysis for Engaging Question Extraction
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Solution Overview
Problem
Digital communication platforms lack the ability to provide analytics data and metrics on engaging questions asked during remote communication sessions, which are crucial for improving sales performance in sales meetings.
Innovation Solution
A system that connects to a communication session, extracts a transcript, identifies and tags engaging questions, and presents data on these questions for display, using linguistic features and organizational affiliations to analyze interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If digital communication platforms record and store transcripts of communication sessions, then the data becomes available for analysis, but the platforms still lack the capability to extract and provide analytics on engaging questions
Solution Approach 1:
The system extracts engaging questions from communication transcripts by identifying specific linguistic features (interrogative words, question marks, syntactic patterns) and separates them from the rest of the conversation data. This extraction process transforms unprocessed transcript data into structured analytics on engaging questions, providing actionable insights without requiring complete reprocessing of all communication data.
Solution Approach 2:
The patent introduces an intermediary processing layer between the transcript storage and the analytics output. This layer includes components that identify linguistic features, determine speaker affiliations, and classify questions as engaging based on predefined criteria. This intermediary process bridges the gap between raw transcript data and meaningful analytics without requiring direct complex processing between storage and presentation layers.
2Measurement precision
If the system analyzes all utterances in communication sessions to identify engaging questions, then comprehensive analytics are provided, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing analysis only on utterances that contain question-like linguistic features rather than processing every utterance in the transcript. The analysis selectively identifies engaging questions based on specific criteria (interrogative words, question marks, syntactic patterns) without performing exhaustive analysis on all communication data, thereby reducing processing time while maintaining identification precision.
Solution Approach 2:
The patent segments the transcript analysis process into distinct stages: identifying interrogative words, detecting question marks, analyzing syntactic patterns, determining speaker affiliations, and classifying engaging questions. This segmentation allows the system to process transcripts through multiple specialized components rather than a single monolithic processor, improving both precision and efficiency by applying appropriate analysis methods to specific segments of the data.
3Productivity
If the system provides detailed analytics on engaging questions including speaker identification and organizational affiliation, then actionable insights are enhanced, but data processing complexity increases
Solution Approach 1:
The system automatically determines speaker affiliations with organizations by analyzing contextual information within the transcript itself, such as introduced speakers, company mentions, and role indicators. This self-service approach allows the system to extract organizational affiliation data without requiring external databases or manual input, reducing system complexity while providing comprehensive analytics on who asked engaging questions and their organizational context.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously refines its identification of engaging questions and speaker affiliations based on patterns detected in the transcript. The analytics provide feedback to users about communication effectiveness, allowing teams to adjust their questioning strategies. This feedback loop enhances productivity by translating raw analytics into actionable sales performance insights without requiring complex external validation systems.
Data Source
AI summary
Methods and systems provide for extracting engaging questions from a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a transcript of a conversation between the participants produced during the communication session; extracts, from the transcript, utterances including one or more sentences spoken by the participants; identifies a subset of the utterances spoken by a subset of the participants associated with a prespecified organization; extracts engaging questions within the subset of utterances, the engaging questions each including a question asked by the participant associated with the organization that is immediately answered in the following utterance by a participant not associated with the organization; and presents, for display at one or more client devices, data corresponding to the extracted engaging questions.