Discussion

Received results of predicting whether a person is lying or telling the truth were surprisingly good. Some models obtained accuracy more than 90%, which is incredibly good result. On the contrary, in the original article highest average accuracy was 63% (combining gaze, EEG and audio/video data). [1]

J Rannap in Truth or lie?

Jan 13, 2020

Conclusion

Detecting deception has been a widespread task for many years as it could be beneficial for many areas (e.g. police, court). In this…

Anneott in Truth or lie?

Jan 13, 2020

Results

Analysis Over Means

In this analysis we took mean over every users all runs. Therefore, in the obtained…

Kristiina Uusna in Truth or lie?

Jan 13, 2020

Data overview

In this section we will look more deeply at the structure of the EEG dataset. The dataset is acquired from the Bag-of-Lies Database…

J Rannap in Truth or lie?

Jan 12, 2020

Methodology

Data Preprocessing

For all classifiers the raw EEG data was preprocessed in various ways in order…

Kristiina Uusna in Truth or lie?

Dec 18, 2019

Background

In this project the Bag-of-Lies data set is used for predicting if participants lied or not. The data set is multimodal, consisting of…

Anneott in Truth or lie?

Dec 18, 2019

Introduction

Deception detection is a task of extreme importance concerning widespread issues of security. Studies are consistent in showing that deception judgement in all types of people is no more accurate than chance. [1,2] Therefore, when dealing with deception, a more precise approach is needed. Deception…

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Truth or lie?

Building different models to assess whether a person is lying based on EEG data.

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