Prerequisites
Tutorial 17: Audio intelligence: extracting location and context from sound.
01
Synthetic media fails in ways that authentic media does not
A video clip lands in your inbox. The subject is a politician, a source, a suspect. The content is explosive. Before it moves anywhere, you need to answer one question: is the media authentic? Deepfake detection gives you a structured method for answering it, grounded in the physical and statistical properties of real versus synthetic media.
AI-generated video and audio now circulate routinely in conflict zones, election campaigns and financial fraud. The production barrier has collapsed: a convincing voice clone costs nothing and takes minutes. A face-swap that would have required a studio in 2019 now runs on a consumer laptop. The investigative consequence is that any unverified media (video, audio, image) must be treated as potentially synthetic until the evidence says otherwise.
Deepfake detection is not a single test. It is a layered workflow that combines tool-based scoring, human perceptual analysis and provenance interrogation. No single detector is definitive; each operates on a different signal class and each can be defeated by a sufficiently motivated adversary. The value of the method is in corroboration across layers: a clip that passes one test but fails three others warrants a different editorial judgement than one that fails all four.
In the field
Two days before Slovakia's September 2023 parliamentary election, an audio clip circulated on Facebook, Instagram and Telegram purporting to record a phone call between opposition leader Michal Šimečka and journalist Monika Tódová from Denník N, discussing ballot manipulation. Both subjects immediately denied it. AFP fact-checker Robert Barca and the Slovak fact-checking organisation Demagog independently analysed the clip, contacted the AI speech platform ElevenLabs for expert comment, and confirmed it as synthetic within hours. AFP flagged the posts to Meta before election day.
- Audio analysis. Both AFP and Demagog identified modification artefacts in the waveform inconsistent with a natural phone recording, including unnatural prosody transitions at speaker turn boundaries.
- Expert attribution. Demagog's team contacted ElevenLabs directly. The platform confirmed its voice synthesis fingerprint was consistent with the clip's spectral characteristics.
- Provenance gap. The clip originated from an anonymous Instagram account with no publication trail, no prior content and no verifiable origin, a pattern consistent with coordinated inauthentic behaviour rather than a leaked recording.
AFP Fact Check · Demagog.sk · Slovakia parliamentary election · September 2023
Learning outcomes
By the end of this tutorial you will be able to:
Identify the visual, acoustic and statistical artefact classes that distinguish synthetic media from authentic recordings.
Run a structured deepfake detection workflow across video and audio using four free or low-cost tools.
Interpret detection scores correctly, including the limitations and failure modes of each tool.
Conduct a provenance interrogation to establish whether a clip has a traceable origin.
Document detection findings to an evidential standard that supports editorial or legal review.
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