Audio Deepfake
The short answer · 17 words
In short
Synthetically generated or manipulated audio that can simulate authentic speech, a speaker identity, or a real event.
Flow-alerta.cab (2026): Audio Deepfake. https://flow-alerta.cab/en/glossar/audio-deepfake. Editorially reviewed on: 09 October 2026.
How much detail would you like?
Practical
High for fraud prevention, approval processes and credible communication. Technical recognition alone is not reliable enough to replace organizational controls.
Example scenario: A supposed voice message from the management calls for an urgent payment. The operation confirms the instruction via a second, predefined channel.
Four-eye clearances, recall procedures and documented identity verification for payment, staff and confidential instructions; training of typical warning signals.
At a glance
- Core
- Audio-deepfakes are created, for example, by text-to-speech or voice conversion and can imitate a real voice or expression. Not every AI-generated audio file is a deepfake: What matters is context, claimed authenticity and possible deception.
- Use
- High for fraud prevention, approval processes and credible communication. Technical recognition alone is not reliable enough to replace organizational controls.
- Example
- Example scenario: A supposed voice message from the management calls for an urgent payment. The operation confirms the instruction via a second, predefined channel.
- Limits
- Calling each synthetic voice a deepfake; mixing replay attack, voice cloning and manipulation; seeing detectors as proof-proof; ignoring compression and unknown generation methods; not securing original file and context.
Questions about this term
Is it safe to recognize audio deepfakes?
Not reliable in every case.
Is every AI voice a deepfake?
No.
Does a password help?
It may be part of a multi-step process, but it does not replace robust identity verification.
All details and background
Audio-deepfakes are created, for example, by text-to-speech or voice conversion and can imitate a real voice or expression. Not every AI-generated audio file is a deepfake: What matters is context, claimed authenticity and possible deception.
ELI5 – Explained simply
An artificially created recording sounds like a real person has said something, even though this recording is not from her.
Why it matters in practice
High for fraud prevention, approval processes and credible communication. Technical recognition alone is not reliable enough to replace organizational controls.
Example
Example scenario: A supposed voice message from the management calls for an urgent payment. The operation confirms the instruction via a second, predefined channel.
Pitfalls and limits
- Calling each synthetic voice a deepfake; mixing replay attack, voice cloning and manipulation; seeing detectors as proof-proof; ignoring compression and unknown generation methods; not securing original file and context.
Origin & history
Voice synthesis and voice conversion evolved over decades. The ASVspoof series launched in 2015 with countermeasures against fake speech; in 2021, it featured its own speech-deepfake track for TTS and voice conversion attacks.
Use in mid-sized companies
- Four-eye clearances, recall procedures and documented identity verification for payment, staff and confidential instructions; training of typical warning signals.
Related terms
- Voice closing
- Text-to-speech
- Provenance
Matching Flow-alerta service
AI adoption & supportAI implementation & support: clarify usage guidelines, limits, responsibilities and escalation paths.Matching tool / use case
View use casesUse Case: Verification of unusual money orders via an independent secondary channel; research resource: ASVspoofSources
- www.asvspoof.orgASVspoof 2021, Evaluation Plan
- arxiv.orgYi et al. (2023), Audio Deepfake Detection: A Survey
Quellenprüfung: 09.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.
Editorially reviewed on: