arXiv:1903.04484
The Truth and Nothing but the Truth: Multimodal Analysis for Deception Detection
원문 초록
We propose a data-driven method for automatic deception detection in real-life trial data using visual and verbal cues. Using OpenFace with facial action unit recognition, we analyze the movement of facial features of the witness when posed with questions and the acoustic patterns using OpenSmile. We then perform a lexical analysis on the spoken words, emphasizing the use of pauses and utterance breaks, feeding that to a Support Vector Machine to test deceit or truth prediction. We then try out a method to incorporate utterance-based fusion of visual and lexical analysis, using string based matching.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Literature Meets Data: A Synergistic Approach to Hypothesis Generation
Automated Tone Transcription and Clustering with Tone2Vec
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Sample
Norface: Improving Facial Expression Analysis by Identity Normalization
Representation Learning and Identity Adversarial Training for Facial Behavior Understanding
Advancing Automated Deception Detection: A Multimodal Approach to Feature Extraction and Analysis
토론
이 논문과 연결된 포럼 글이 아직 없습니다.