Guide-linked quiz · Medium Level

Speaker Verification Quiz

Review one-to-one speaker verification, enrollment references, operating thresholds and spoofing countermeasures. in biometric workflows.

Related guide pathsSpeaker Verification
Question 1 of 8

Speaker verification is best described as which type of decision?

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  1. Speaker verification is best described as which type of decision?
    • One-to-one: does this voice match the claimed identity?
    • One-to-many: whose voice is this?
    • Transcribing speech to text
    • Detecting silence in audio
  2. What is the difference between text-dependent and text-independent verification?
    • One uses video, the other audio
    • Text-dependent requires a fixed passphrase; text-independent works on any speech
    • Text-dependent is for music only
    • There is no difference
  3. What does the Equal Error Rate (EER) represent?
    • The total number of users
    • The audio sample rate
    • The point where false accepts equal false rejects
    • The length of the passphrase
  4. Why is anti-spoofing important in speaker verification?
    • To compress audio faster
    • To translate languages
    • To increase passphrase length
    • To defend against recordings and AI-generated deepfake voices
  5. What is a stored "voiceprint" used for in verification?
    • Serving as the enrolled reference the test voice is compared against
    • Playing back the user's speech
    • Compressing the audio file
    • Translating speech to text
  6. Lowering the acceptance threshold typically does what?
    • Rejects more genuine users and blocks more impostors
    • Accepts more impostors while accepting more genuine users
    • Has no effect on errors
    • Only changes the audio length
  7. What does an ASVspoof evaluation test in addition to ordinary speaker matching?
    • Whether the speaker’s words are grammatically correct
    • Whether the microphone has a camera
    • Whether countermeasures can detect replayed or synthesized spoofed speech
    • Whether the voice belongs to a known language
  8. Why does a speaker match score not prove that a live person spoke the audio?
    • Speaker embeddings contain the speaker’s legal name
    • A match score measures camera presence
    • Verification does not analyze audio
    • A recording or synthetic voice may imitate the enrolled speaker

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