NLP Personality Assessment Device Reducing Response Distortion
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Solution Overview
Problem
Conventional self-report personality tests are susceptible to response distortion and bias, making them unreliable, especially in contexts like job interviews and criminal assessments where honesty may be compromised.
Innovation Solution
An NLP-based personality assessment device and method that includes a questionnaire providing unit, preprocessing unit, and personality prediction unit, using scientifically verified psychological theories and high-quality data from direct interviews to analyze subjective responses and predict personality traits, minimizing noise even with small sample sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-report personality tests are used, then the assessment is simple and highly serviceable, but response distortion and bias occur making it easy for examinees to distort or bias responses
Solution Approach 1:
The patent introduces an intermediary system (NLP-based automated assessment device) that mediates between the examinee and the personality assessment. This intermediary analyzes natural language responses objectively, preventing direct manipulation of results while maintaining ease of administration. The system acts as an impartial mediator that processes language patterns to reveal genuine personality traits without human bias or examinee manipulation.
Solution Approach 2:
The patent replaces the mechanical system of manual self-reporting with an automated natural language processing system. Instead of relying on examinees to manually select or describe traits (which can be manipulated), the system uses NLP algorithms to analyze language patterns, word choices, and response structures to automatically infer personality characteristics, thereby eliminating response distortion while maintaining serviceability.
2Ease of operation
If self-report personality tests are used, then the assessment is simple to administer, but face validity is too high making it easy for examinees to distort responses
Solution Approach 1:
The NLP-based assessment system serves as an intermediary that objectively analyzes language patterns without being influenced by examinee awareness of assessment goals. This mediator processes nuanced linguistic features that reveal genuine personality traits, preventing examinees from successfully faking responses while maintaining simple administration through automated online delivery.
Solution Approach 2:
The patent changes the measurement parameters from direct self-reporting of traits to indirect analysis of language patterns. Instead of asking examinees to directly report personality characteristics (which they can manipulate), the system analyzes parameters such as word choice frequency, sentence structure, response length, and linguistic complexity to infer personality traits, thereby improving measurement precision while keeping administration simple.
3Measurement precision
If NLP-based analysis with small sample size is used, then input noise is minimized, but data collection requires direct interviews by researchers
Solution Approach 1:
The patent applies preliminary action by pre-processing and cleaning the training data through rigorous filtering and validation procedures before model development. This preliminary data preparation minimizes noise and ensures high quality input for the NLP model, allowing accurate personality assessment even with smaller sample sizes. The preprocessing steps include removing irrelevant data, standardizing formats, and validating data quality before analysis.
Data Source
AI summary
Disclosed is a natural language processing (NLP)-based personality assessment device. The personality assessment device includes a questionnaire providing unit configured to transmit, to a terminal, a message that includes a plurality of interview questions and at least one directive sentence and to receive, from the terminal, a first response to each of the plurality of interview questions and a second response to the at least one directive sentence; a preprocessing unit configured to preprocess at least one of the first response and the second response; and a personality prediction unit configured to predict personality of a user of the terminal using a preprocessing result by the preprocessing unit.