Transcript Analyzer System for Contradiction Detection

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Solution Overview

Problem

Current methods for analyzing transcripts, whether manual or computer-assisted, are time-consuming and ineffective in identifying nuanced connections and contradictions within and across transcripts, requiring improved technology for accelerated review and enhanced insight.

Innovation Solution

A transcript analyzer system comprising a natural language processing module, semantic analyzer, clustering module, and contradiction detection algorithm, which uses multi-genre natural language inference datasets and hierarchical DBSCAN clustering to identify themes, contradictions, and inconsistencies, and provides interactive user interfaces for efficient analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual review methods are used to analyze transcripts, then reviewers can identify context and connections, but the process is time-consuming and teams are unable to identify nuanced connections

Engineering Contradiction:

Improveidentification accuracy of connections and contradictionsVSAvoidtime required for transcript review

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical review processes with an automated computer-based system that uses natural language processing, semantic analysis, and contradiction detection algorithms to analyze transcripts, thereby eliminating the time-consuming manual review while maintaining or improving identification accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary computational system that acts as a bridge between raw transcript data and human reviewers, using NLP modules and semantic analyzers to pre-process and highlight key connections and contradictions, thus reducing the time burden on reviewers while improving detection capability

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If teams of reviewers are deployed to analyze transcripts, then more coverage is achieved, but the process remains time-consuming and nuanced connections are still missed

Engineering Contradiction:

Improvetranscript analysis throughputVSAvoidtime required for transcript review

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent enables the transcript analysis system to perform self-service through automated NLP processing, semantic analysis, and contradiction detection without requiring human reviewers for every transcript, thereby increasing productivity while reducing the time investment needed per transcript

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent substitutes human reviewer teams with an automated computational system that can process multiple transcripts simultaneously using parallel computing and algorithmic analysis, thereby achieving higher throughput without the time costs associated with coordinating and managing human review teams

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If manual review is used to identify contradictions, then some inconsistencies are found, but nuanced connections and contradictions in distinct portions of testimony are missed

Engineering Contradiction:

Improvedetection accuracy of contradictionsVSAvoidcomplexity of analysis system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces simple manual contradiction checking with a sophisticated but automated computational system that uses semantic analysis, vector space modeling, and contradiction detection algorithms to identify nuanced contradictions across distinct portions of testimony, thereby improving detection accuracy while managing system complexity through automation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Productivity

If automated NLP systems are implemented for transcript analysis, then review speed increases, but the system must process and analyze large volumes of text data efficiently

Engineering Contradiction:

Improvetranscript review speedVSAvoidcomputational resources required for analysis

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The patent segments the transcript analysis process into distinct modular components including NLP processing, semantic analysis, theme extraction, and contradiction detection, allowing each module to process data independently and efficiently, thereby increasing review speed while optimizing computational resource usage through divided processing tasks

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20240086640A1Method, system, and computer readable storage media for transcript analysis

Publication Date: 2024.03.14 LEXITAS INC

AI summary

A method, system, and non-transitory computer-readable storage medium for analyzing transcripts includes receiving a first transcript having one or more questions and one or more answers to the one or more questions, ingesting the first transcript into a first transcript data file, the transcript data file based at least in part on the first transcript, using natural language processing to extract transcript data from the first transcript, generating one or more sets of metrics corresponding to the first transcript, the one or more sets of metrics based at least in part on global metadata of the first transcript data file, contextualizing the first transcript using vector space modeling, and executing a contradiction detection assessment based at least in part on the one or more questions and the one or more answers to the one or more questions, using inference modeling and anomalies detection to determine a contradiction score.