---
license: cc-by-4.0
library_name: mlx
tags:
  - mlx
  - speaker-diarization
  - witness
---

# witness-diarize-plda-redimnet2

Big-corpus (921-speaker, LibriSpeech-refit) PLDA fit for the ReDimNet2-B6
x-vector space, in the raw little-endian `*.f32` blob layout the witness VBx
backend loads (community-1 layout). Pairs with
`littlebearlabs/witness-redimnet2-b6-mlx` for VBx clustering.

## Attribution

- **Fit**: ours — `.research/diarization/fit_resnet293_plda.py` +
  `gen_plda_vbx_fixtures.py`, refit on a 921-speaker corpus in the
  ReDimNet2-B6 192-d x-vector space.
- **Method / layout**: BUT VBx (variational Bayes HMM x-vector clustering) +
  the pyannote `community-1` PLDA file layout. The ReDimNet2-B6 embedder these
  x-vectors come from is MIT (PalabraAI); the VBx method and the community-1
  layout are the upstream references.
- **License**: CC-BY-4.0 (our fit; attribute witness + the BUT VBx / community-1
  lineage).

## What's in this repo

Six raw little-endian f32 blobs (the full set the VBx backend loads):

- `transform_mean1.f32` (xvec_dim=192)
- `transform_lda.f32`   (192·128)
- `transform_mean2.f32` (128)
- `plda_mu.f32`         (128)
- `plda_tr.f32`         (128·128)
- `plda_psi.f32`        (128, the across-class covariance diagonal)

---

*Converted to MLX for [witness](https://github.com/littlebearlabs/witness), an
open-source Rust toolkit for on-device system capture on macOS. Generated by
`.research/diarization/publish_weights.sh`.*