Audio Deepfake Detection Quiz

Answers and explanations appear as you take the quiz.

1. What is the core goal of an audio deepfake detector?
   • To decide whether speech is real or AI-synthesized
   • To improve the sound quality of a recording
   • To transcribe speech into text
   • To compress audio files
2. In “Does Audio Deepfake Detection Generalize?”, which feature comparison improved performance in the authors’ controlled evaluation?
   • Raw transcript tokens instead of audio
   • CQT or log-spectrogram features instead of mel-spectrogram features
   • A larger waveform file instead of a smaller one
   • Video frames instead of speech features
3. Why is audio deepfake detection described as an 'arms race'?
   • Detectors are run on military hardware
   • Audio files keep getting larger
   • New synthesis methods evade detectors trained on older fakes
   • It requires two people to operate
4. What does the well-known ASVspoof benchmark evaluate?
   • Music recommendation quality
   • Text translation accuracy
   • Image generation realism
   • Anti-spoofing/deepfake detection for speech
5. What can a valid C2PA Content Credential help a verifier check?
   • A signed record of an asset’s provenance and edit history
   • That every spoken claim in the audio is true
   • The speaker’s real-world identity in all cases
   • That a recording has never been compressed
6. What input type did the ASVspoof 2021 Deepfake task target?
   • Uncompressed music recordings from a studio
   • Manipulated, compressed speech posted online
   • Images altered by face-swapping systems
   • Only live telephone conversations with known speakers
7. How large was the real-world dataset collected in the cited audio deepfake generalization study?
   • 3.79 hours total, all authentic speech
   • 37.9 hours of deepfakes with no authentic audio
   • 37.9 hours total, including 17.2 hours of deepfakes
   • 172 hours total, including 17.2 hours of deepfakes
8. What does the absence of a C2PA credential establish?
   • That the recording is necessarily a deepfake
   • That the recording has no edits
   • That the speaker is verified
   • Nothing by itself about whether the media is authentic or synthetic