Instructions to use tinypocket/akouo-speaker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- WhisperKit
How to use tinypocket/akouo-speaker with WhisperKit:
# Install CLI with Homebrew on macOS device brew install whisperkit-cli # View all available inference options whisperkit-cli transcribe --help # Download and run inference using whisper base model whisperkit-cli transcribe --audio-path /path/to/audio.mp3 # Or use your preferred model variant whisperkit-cli transcribe --model "large-v3" --model-prefix "distil" --audio-path /path/to/audio.mp3 --verbose
- Notebooks
- Google Colab
- Kaggle
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license: cc-by-4.0
pretty_name: akouo — speaker diarization (Core ML)
viewer: false
library_name: whisperkit
tags:
- speakerkit
- pyannote
- diarization
- speaker-diarization
- coreml
---
# akouo — speaker diarization (Core ML)
Core ML speaker segmentation and embedding models, used by
[akouo for iOS](https://github.com/tinypocket/akouo-ios) to work out who spoke when — entirely on
device.
This is a **mirror**, hosted so the app does not depend on a third-party repository at runtime.
The weights are unmodified.
## Provenance
- Converted to Core ML by **Argmax**, from
[argmaxinc/speakerkit-coreml](https://huggingface.co/argmaxinc/speakerkit-coreml).
- Derived from **pyannote** speaker models.
- Runs via SpeakerKit, part of [WhisperKit](https://github.com/argmaxinc/WhisperKit) (MIT).
## Licence — attribution required
**CC-BY-4.0.**
The upstream pyannote models carry mixed terms: `pyannote/segmentation-3.0` is MIT, while
`pyannote/wespeaker-voxceleb-resnet34-LM` and `pyannote/speaker-diarization-community-1` are
CC-BY-4.0. Where bundled components differ, the most restrictive governs — so CC-BY-4.0 applies to
this repository as a whole.
**If you redistribute these weights or ship them inside an application, you must credit pyannote
visibly.** This is a condition of the licence, not a courtesy.
Argmax does not declare a licence on the source repository. The licence stated here is a good-faith
reading of what these weights derive from, not a grant by tinypocket.
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