Prospero – A Credibility Assessment Aid

Unveil the hidden truths

Introducing Prospero – A Credibility Assessment Aid

An integrated hardware-software system designed for law enforcement agencies to aid in credibility assessment during investigative interviews. A suite of discreet, non-invasive sensors captures facial expressions and vocal patterns, which are then streamed in real time and recorded for post-mortem analysis. The system provides investigators with insights into potential signs of deception or truthfulness, enhancing the efficiency and accuracy of investigations.

Team members

Jarrod Lim (EPD), Lim Fuo En (CSD), Lim Rui-Chong Anthony (CSD), Charlotte Ng Si Min (CSD), Moey Wan Wei, Adric (EPD), Issac Jose Ignatius (CSD), Yong Zheng Yew (CSD)

Instructors:

  • Park Jihong

Writing Instructors:

  • Belinda Seet

Can we trust them? Let's find out...

Motivation

During investigative interviews, investigators need to balance questioning the suspect and verifying the credibility of the suspect’s statement. This results in high mental workload for investigators that can result in missing of information critical to solving the case. Furthermore, current credibility assessment tools are often bulky, invasive and cumbersome, making them impractical for most investigation cases.

Current Investigative Interview Practice

Investigative Interviews are often long, complex and tiring. Here are the 3 main stages.

Interview
  • Investigators engage with the suspect by asking questions, taking down notes and building rapport
Post-Interview Analysis
  • Investigators review and analyze the notes taken during the interview
  • Decide if they would require a follow up interview to confirm some suspicions
  • There is no reviewing of the interview in its entirety
Additional Credibility Assessment Test (Polygraph)
  • If deemed necessary, follow up interview with the suspect is carried out
  • Polygraph test used to determine the suspect's credibility

Key Challenge: Interview Process

During the investigative interview process, investigators face many key challenges. Here are just 2 of the many.

High Mental Workload

Investigators have to juggle multiple tasks during investigative interviews. Such tasks include:

  1. Questioning the suspect
  2. Noting down responses
  3. Observing facial, verbal, and body cues to assess credibility
  4. Coming up with questions to drive the interview

Uncooperative Behaviour

Sometimes, the suspect may display uncooperative behaviour during interviews. Such behaviour include:

  1. Refusal to answer questions
  2. Shouting
  3. Attempts to deceive and misleading investigators
  4. Feigning ignorance

Key Challenge: Current Technology

The polygraph is the current tool that is used in investigative interviews to assess truthfulness or deception by measuring physiological changes in a person’s body. The polygraph has its limitations, and of them examples are:

Problem Statement

How might we create an integrated credibility aid that is contactless, discreet and accessible to augment the current common interview practices?​

Key Requirements for our Solution

To better customize our solution to investigators, our solution must be:

Prospero's system and sensors cannot touch the suspect during operation

Prospero should not interrupt the workflow of the investigators during the interview and should not be easily identifiable by the suspect

Prospero's system can be set up seamlessly and the outputs should be easily understandable by investigators

Background: Physiological Indicators

Literature reviews indicate that both facial expressions and speech patterns provide valuable insights into a person’s credibility. Micro-facial expressions can be used to capture facial cues, while speech patterns can be analyzed using Layered Voice Analysis. Let’s dive into them.

Micro-Facial Expressions (MFE)

What are MFEs?

MFEs are quick and subtle facial expressions that last for up to half a second. Due to their spontaneous nature, they are usually expressed when individuals try to hide their genuine emotions. Giving investigators access to MFE data allows them to make inferences from context about what a suspect might be concealing.

Facial Action Coding System (FACS) is a comprehensive and objective method to measure and classify facial movements developed by Paul Ekman. It works by breaking down each expression into specific muscle movements known as Action Units (AUs).

What are AUs?

AUs are the movement of a facial muscle or muscle groups that make up an emotion. 

They enable the capture of precise descriptions of all expression types. 

We developed an AI-powered automated MFE detection system which maps images to their corresponding AUs

Layered Voice Analysis (LVA)

LVA is a patented and proprietary tool developed by Nemesysco that analyzes vocal patterns.

Features

Most helpful feature: The Coloured Bar

Different colours correspond to different levels of deception risk, and the most important colours are:

  • Orange indicates medium deception risk
  • Red indicates high deception risk

Investigators look out for the orange and red coloured segments to help them ascertain whether someone has deceptive intentions. We seek to integrate LVA into our solution.

So, how are we solving the problem?

Hardware Solution: SpyFlask

Software Solution: Prospero Analyser

Introducing: SpyFlask

Now that we know what to indicators to analyse and how we are analysing them, we need a way to get the data in an accurate and optimal way.

Technical Requirements to meet

  • MFE requires a clear image of the interviewee’s face
  • LVA requires a clean audio signal of only the interviewee, since having the interviewer’s audio could corrupt the analysis

Features

Audio and Visual Recordings
  • Video records at 720p, 60fps
  • Audio recorded using directional microphones
  • Ensures we have noise isolation of only the interviewee for accurate LVA analysis
Wireless Streaming
  • Live streaming of audio and video feed via RTSP and WebRTC protocol
  • Functions on a Local Area Network
Facial Tracking
  • Computer vision model to identify and track interviewee's face
  • Motorized gimbal system to rotate the camera module
  • Ensures interviewee's face is centered for accurate MFE analysis
clear label ref label

Introducing: Prospero Analyser

Prospero Analyser, our frontend, is a visualization tool to visualize recorded interviews from SpyFlask and analyses from MFE and LVA, empowering interviewers to move beyond raw data.

Start Recording Live Interviews

End Recording Live Interviews

View Interview Analysis Data

Managing All Interview Analyses

Overall System Architecture

The video and audio inputs are live streamed from SpyFlask to Prospero Analyser. It is the bridge between our hardware and software. Below, the detailed system architecture shows the technologies we used and interactions between our individual components as well as the data flow path.

Testing and User Reviews

We devised a testing plan aimed to evaluate how well Prospero answered our Problem Statement. Here is what our users had to say.

Enhancement: How does Prospero add value to the current interview practices and post-interview analysis?

Prospero was found to have provided the convenience of a combined analysis as well as a second opinion

"Check for discrepancies between the MFE and LVA bars"
user-3296
HTX Contractor
"Used to double confirm my intuition"
user-3296
Ex ICA Officer

Discretion: How disruptive is Prospero during interviews?

Prospero was deemed to be unobtrusive and the typical interview scenario flow was not disrupted

"Investigators can bring in a flask, not a massive camera"
user-3296
HTX Contractor
"Doesn't disrupt my process or change the questions asked"
user-3296
Ex ICA Officer

Accessibility: Can investigators use Prospero with minimal training?

Interviewers were able to use Prospero in their interviews with ease and could setup everything on their own

"Cuts down the set up time in half"
user-3296
HTX Contractor
"Rather simple process, not much hiccups"
user-3296
HTX Contractor

Prospero's Value Proposition

Why choose us?

In addition to their initial judgement, investigators can rely on Prospero to give them a second opinion.

The burden of looking out for fleeting facial expressions and listening for vocal cues is offloaded, allowing investigators to engage in conversation with the suspect more naturally.

Prospero does not disrupt current interview processes. It just sits on the table, silently recording information.

Prospero has an easy start up procedure - all we need is a click of a button and in the blink of an eye, the live feed is shown on Prospero Analyzer.

Prospero's recording capabilities are well obscured by the disguise of an everyday object, a bottle. 

All in all, Prospero brings automatic streaming with a combined analysis that empowers interviewers and most importantly, continues to enable human connection.

Poster

In partnership with :

Supported by :

Acknowledgements

The team would like to extend our heartfelt gratitude to the following people for their unwavering support throughout our project which were pivotal to Prospero’s success.

Associate Professor Park Jihong, our Capstone Mentor, for his invaluable guidance and support on the overall direction and development of our project.

Ms Belinda Seet, our Centre for Writing and Rhetoric Mentor, for her patient mentorship in helping us refine our presentation materials, communication skills and reports.

Mr Kee Ein Cern, Mr Shaun Wee, Mr Jared Tin, Ms Simran Kaur, our Industry Mentors, for their exceptional guidance, support, and mentorship throughout the development of our project, and for providing us with the unique opportunity to work on such an impactful initiative.

Last but not least, our friends, families, and loved ones, who displayed unrelenting support throughout and stood by us every step of the way.

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Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

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8 Somapah Road Singapore 487372

8 Somapah Road Singapore
487372

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Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

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Log in to your existing account.