VeriScope
This tool is restricted to authorised users.
Enter the access password to continue.
Before you continue, please note:

Once downloaded to your device, VeriScope runs entirely locally in your browser. It is not connected to any AI system, external server, or the internet — all analysis uses fixed, rule-based pattern matching contained within this file. No transcript data, case details, or other input is transmitted anywhere.

All scores, classifications, and narrative summaries generated by this tool are indicative only. ETiCA Global accepts no responsibility for the accuracy, completeness, or reliability of any analysis produced by VeriScope. Every finding must be independently reviewed and verified by a qualified practitioner before being relied upon for any professional, legal, or investigative purpose.

Interview Details

Case Information
Interviewing Officer
Recording Details
Breaks
#StartEndDuration (mins)Reason
Total break time: 0 mins  |  Net interview time:

Persons Present

All Persons in Interview
Include all persons present at any point: interviewers, interviewee, legal representatives, appropriate adults, interpreters, observers.
RoleName / InitialsRank / TitleOrganisationTraining LevelEntire Interview
No persons added yet.

Interviewee Profile

This information contextualises the analysis. It is stored locally only — never transmitted.
Interviewee Characteristics
Mental Health Conditions (as reported or known)
Neurodivergence & Cognitive Considerations
Physical Health & Other Considerations

Transcript / Audio / Video Recording

Transcript Entry
VeriScope needs speaker labels at the start of each line. Interviewer: INT:  I:  INTERVIEWER:  OFFICER:  DC:  Q:  or any rank/name followed by a colon (e.g. DC Jones:)
Interviewee: S:  SUB:  SUBJECT:  SUSPECT:  WITNESS:  VICTIM:  A:  R:
Also accepted: timestamps before labels (e.g. [00:14] INT:) and bare Q / A format used in legal transcripts.
📊
Complete the interview details and transcript, then click Run VeriScope Analysis.
Overall Interview Quality Score
/ 100
How is this score calculated?

The overall score is a weighted composite of five dimensions, each scored 0–100:

Dimension Weight How it is measured
Question quality 30% Up to 70 pts for productive ratio; +20 pts for open invitation (TED) proportion; penalties for leading (−30), multiple (−20), forced-choice (−15) and opinion/statement (−10) questions
Rapport & empathy 20% +10 pts per ground-rules utterance; +12 pts per empathic continuer (EOC); −20 pts per empathic terminator (EOT). Built from detected behaviours only — no baseline offset
Non-coerciveness 25% Starts at 100; −15 pts per detected instance of coercive or oppressive language (threats, minimisation, evidence bluffs, persistent re-asking)
Silence / pausing 10% Starts at 100; −20 pts per detected premature interruption of the interviewee (Shepherd, 2007 — "filling the pause")
Méndez compliance 15% Each of 7 Méndez Principles assessed as met / partial / not met from transcript patterns and form data. Score calculated proportionally from statuses

Scores are generated automatically from transcript analysis and should be interpreted as indicative indicators, not definitive judgements. Manual amendments to question types (using the dropdown in the utterance log) will update the scores on re-analysis. Framework references: Oxburgh, Myklebust & Grant (2010); Griffiths & Milne (2006); Shepherd (2007); Méndez Principles (UN, 2021).

Utterance-by-Utterance Analysis Log
Every utterance is classified. Filter by type. Hover truncated text to read in full. Concern-type utterances are highlighted.
Question Type Analysis (Oxburgh, Myklebust & Grant, 2010)
Question Flow — Radial Spiral Each arc = one interviewer utterance, clockwise from 12 o'clock
Rapport & Empathy Analysis (Oxburgh & Ost, 2011; Barrett-Lennard, 1981)
Breaks Summary
Méndez Principles Compliance
Coercive / Oppressive Language
Use of Silence & Pausing
Speaking Time Distribution
Vulnerability & Adaptations
Expert Narrative Summary
🎯 Reflective Learning & Development Based on your interview data