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Looking for Lies: An Exploratory Analysis for Automated Detection of Deception [Minkštas viršelis]

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  • Formatas: Paperback / softback, 92 pages, aukštis x plotis x storis: 254x178x5 mm, weight: 177 g, Illustrations, unspecified
  • Išleidimo metai: 31-Dec-2022
  • Leidėjas: RAND Corporation
  • ISBN-10: 1977409520
  • ISBN-13: 9781977409522
Kitos knygos pagal šią temą:
Looking for Lies: An Exploratory Analysis for Automated Detection of DeceptionDidesnis paveikslėlis
  • Formatas: Paperback / softback, 92 pages, aukštis x plotis x storis: 254x178x5 mm, weight: 177 g, Illustrations, unspecified
  • Išleidimo metai: 31-Dec-2022
  • Leidėjas: RAND Corporation
  • ISBN-10: 1977409520
  • ISBN-13: 9781977409522
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781977409522.html
Raktažodžiai:

The authors of this report developed and tested the use of machine-learning methods to detect speech patterns that reflect attempts at deception or truthfulness during simulated security clearance background interviews.

About This Report iii
Figures and Tables
vii
Summary ix
Chapter One Introduction
1(2)
Study Background
1(1)
Report Outline
2(1)
Chapter Two Relevant Background Literature
3(10)
Select Literature on Detecting Deception
3(5)
Machine Learning for Detecting Deceptive Speech
8(2)
Summary
10(3)
Chapter Three Description of Data
13(6)
Sample and Procedures
13(2)
Interview Technique
15(2)
Analysis of Interview Data
17(2)
Chapter Four Results from Analysis of Interview Data
19(20)
Background of the Linguistic Models
19(2)
Analysis of Virtual Teleconference Interviews
21(11)
Analysis of Virtual Chat Interviews
32(6)
Summary of Key Findings
38(1)
Chapter Five Potential Sources of Bias
39(8)
Research Finds Gender Might Affect How People Are Deceptive
39(4)
Does the Interviewer's Gender Matter?
43(1)
Implications and Key Considerations
44(3)
Chapter Six Limitations, Conclusions, and Recommendations
47(6)
Limitations
47(2)
Conclusions and Recommendations
49(1)
Potential for Next Steps
50(3)
APPENDIXES
A Modified Cognitive Interviewing
53(2)
B Study Materials
55(6)
C Example Output from Amazon Web Services Transcribe
61(4)
D Proof of Concept: Deep Learning Contradiction Model
65(10)
Abbreviations 75(2)
References 77