Making audiovisual quality control more reliable
How do you decide whether a video can be broadcast, using reproducible checks and traceable evidence?
3500 € per session, excl. VAT
In short
Over two days, comprising 14 hours excluding breaks, design a prototype audiovisual approval workflow combining technical, editorial and legal checks. You will build a decision matrix, use generative AI to structure observations, then test the system on fictional videos before preparing a limited pilot.
Why this training?
A playable export may still be unsuitable for distribution: poorly intelligible dialogue, incompatible framing, incomplete subtitles or missing permission. A visual assessment alone is not enough to justify acceptance. Generative AI can help organise criteria and summarise documented issues. It does not replace technical measurements, listening checks or rights verification; a human remains responsible for every decision. Running case study: Avelune Médiation, a fictional organisation, is preparing three short museum videos for screens and social media. Some versions contain mistimed subtitles, music without supporting documentation and an undisclosed synthetic voice. The team must decide whether they can be distributed. Transfer to the workplace: Then launch a pilot on a small, authorised batch: dual approval, tracking of missed defects and a review of thresholds before any extension of the workflow.
Objectives of this training
- Formalise requirements for each distribution channel
- Build a checklist with thresholds and evidence
- Prototype an AI-assisted approval workflow
- Test defect detection and disagreements
- Plan a pilot with responsibilities and indicators
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Video production and post-production managers
- Audiovisual quality leads and editorial managers
Prior skills
- Be proficient in the stages of video editing, export and delivery.
- Know how to use generative AI and verify its responses.
- Understand the editorial constraints of your channels.
What you will work on
Define acceptability
Objective: Distinguish compliance from aesthetic preference. Channels, audiences, versions and blocking defects.
Equip technical checks with measurement tools
Objective: Choose measurements suited to the specifications. Resolution, frame rate, codec, audio levels, synchronisation and artefacts.
Check meaning and accessibility
Objective: Characterise perceptual and editorial defects. Intelligibility, continuity, accuracy, legibility and subtitle synchronisation.
Check provenance and permissions
Objective: Identify grounds for suspension. Music rights, consent for image/voice use, applicable notices, deepfakes and traceability.
Assemble the decision matrix
Objective: Make judgements reproducible. Severity, thresholds, justified exceptions and evidence.
Set boundaries for generative assistance
Objective: Structure observations without inventing findings. Source-based instructions, multimodal limitations depending on availability, confidentiality.
Prototype the workflow
Objective: Assign responsibility for approvals and feedback. Submission, version control, correction, cross-checking and human sign-off.
Run the comparative test
Objective: Measure defect detection coverage. Annotated reference corpus and dual independent assessment.
Analyse discrepancies
Objective: Correct ambiguous criteria. Missed defects, false alerts, disagreements and checking time.
Prepare the pilot
Objective: Limit risk before expansion. Scope, workload, indicators, escalation and termination.
What you take away
- Version-controlled audiovisual acceptance checklist
- Workflow prototype with roles and stop points
- Test report with timestamped issues
- Pilot plan and indicator table
Method and assessment
- Short instructional sessions followed by immediate practice on the case study used throughout.
- Individual work followed by work in pairs, with peer review of the outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Prepare anonymised broadcast specifications and a sample acceptance test form. Check access to a tool authorised by your organisation; use only fictitious or anonymised cases.
Observable criteria: Each requirement has a method, a threshold and expected evidence. ; Each anomaly specifies the version, timecode, severity and decision. ; Missing rights or consent trigger a documented block. ; Detected defects, missed defects and false alerts are counted. ; The pilot specifies the scope, those responsible and the termination conditions..
Frequently asked questions
Does AI approve a video on its own?
No, acceptance remains a human decision based on evidence.
Do the files need to be analysed directly using AI?
No, timestamped observations are sufficient to prototype the assistance.
How should a deepfake be handled?
Check consent, provenance and disclosures; suspend broadcasting if necessary.
Will the workflow be implemented at production scale?
No, the two days produce a tested prototype and a pilot plan.
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