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Speaker Identification and Verification

Recognizing who is speaking from their voice: verifying a claimed identity, picking a speaker from a known group, or splitting a recording by speaker.

Also speaker recognition · voice biometrics · speaker verification · speaker diarization · voiceprint · x-vectors

Fig. / How it works
Voice sampleVoice sampleSpeaker embeddingSpeaker embeddingCompare with enrolledCompare with enrolledSame person?Same person?
Role · kind
Using and applyingConcept
Level
Intermediate

You can tell a friend's voice on the phone before they say their name. Speaker recognition teaches a computer the same trick, using the shape and texture of each person's voice.

Where it fits

Speech and AudioSpeech and AudioEmbeddingEmbeddingSpectrogramSpectrogramSpeaker Identification and Veri…
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How it works

Speech recognition asks what was said. Speaker recognition asks who said it.

Three related tasks:

  • Verification: “Is this really Alice?” Compare the voice with Alice’s enrolled sample.
  • Identification: “Which of our 50 employees is this?”
  • Diarization: “Who spoke when?” in a recording with several people.

Modern systems all rely on speaker embeddings: a neural network listens to a few seconds of audio (as a spectrogram) and outputs a vector that captures the voice, not the words. Recordings of the same person land close together in this embedding space; deciding “same speaker or not” becomes measuring a distance, the same idea as in face recognition. Before deep learning, voices were modeled with Gaussian mixture models.

The big caveat today: text-to-speech voice cloning can imitate a person from a short sample, so banks and others that relied on “my voice is my password” have had to add stronger checks.

Everyday use cases

  • Case 01

    Personalized smart speakers

    A home assistant recognizing which family member is asking, to read out the right calendar.

  • Case 02

    Meeting transcripts

    Labeling "Speaker 1" and "Speaker 2" in a recorded call (diarization).

Strengths, weaknesses and when to use it

Strengths

  • Works hands-free and remotely, with only a few seconds of audio.

Weaknesses

  • Voice cloning makes spoofing much easier, so voice alone is now a weak password.
  • Colds, noise and microphones change how a voice sounds.

When to use itPersonalization and transcripts; for security, only combined with other factors and anti-spoofing checks.

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Check yourself

  1. Q01

    What does speaker diarization answer?

    Show answer

    A: Who spoke when

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