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thescrabi/kaldi_voxceleb_pytorch

Analysis updated 2026-07-17 · repo last pushed 2023-07-06

★ 5PythonAudience · researcherComplexity · 5/5DormantSetup · hard

TLDR

A PyTorch-based speaker identification and diarization system, trained on the VoxCeleb dataset, that figures out who is talking in an audio recording.

Mindmap

mindmap
  root((repo))
    What it does
      Speaker identification
      Speaker diarization
      Voice pattern learning
    Tech stack
      Python
      PyTorch
      Kaldi
    Use cases
      Voice authentication research
      Speaker aware transcription
      Privacy speaker detection
    Audience
      Speech researchers
      ML engineers
    Extras
      Angular Softmax
      Attention layer

Code map

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What do people build with it?

USE CASE 1

Train a neural network to recognize which known speaker is talking in an audio clip.

USE CASE 2

Split a long recording into segments by speaker (diarization).

USE CASE 3

Experiment with Angular Softmax and attention layers for speaker recognition research.

USE CASE 4

Build a speaker-aware transcription or voice authentication prototype.

What is it built with?

PythonPyTorchKaldiLinux

How does it compare?

thescrabi/kaldi_voxceleb_pytorch1ncendium/aibusteraaronmayeux/ha-hurricane-tracker
Stars555
LanguagePythonPythonPython
Last pushed2023-07-06——
MaintenanceDormant——
Setup difficultyhardmoderateeasy
Complexity5/53/52/5
Audienceresearcherops devopsgeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires Kaldi, PyTorch with GPU support, specific datasets, and Linux, aimed at researchers, not casual users.

Copy-paste prompts

Prompt 1
Explain how Angular Softmax helps a speaker recognition model compared to standard softmax.
Prompt 2
Walk me through setting up Kaldi and PyTorch with GPU support to run this speaker identification project.
Prompt 3
How would I adapt this VoxCeleb-trained model to identify speakers in my own audio dataset?
Prompt 4
What does speaker diarization mean and how does this project perform it?

Frequently asked questions

What is kaldi_voxceleb_pytorch?

A PyTorch-based speaker identification and diarization system, trained on the VoxCeleb dataset, that figures out who is talking in an audio recording.

What language is kaldi_voxceleb_pytorch written in?

Mainly Python. The stack also includes Python, PyTorch, Kaldi.

Is kaldi_voxceleb_pytorch actively maintained?

Dormant — no commits in 2+ years (last push 2023-07-06).

How hard is kaldi_voxceleb_pytorch to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is kaldi_voxceleb_pytorch for?

Mainly researcher.

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