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zant-diarize-fluidaudio
aaronslepecky/zant-diarize-fluidaudio
zant-diarize-fluidaudio is a machine learning model from aaronslepecky. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
--- language: en license: mit tags: - speaker-diarization - audio - fluidaudio - ios libraryname: fluidaudio ---
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At a glance
- Access
- Public
- Created
- Oct 2, 2025
- Updated
- Oct 2, 2025
- SHA
- 508850e8
Model card
From the Hugging Face model README
language: en license: mit tags: - speaker-diarization - audio - fluidaudio - ios library_name: fluidaudio
ZantOS FluidAudio Diarization Model
Production speaker diarization model for ZantOS iOS app using FluidAudio.
Model Details
- ID: zant-os/zant-diarize-fluidaudio
- Version: 0.6.1
- Backend: FluidAudio + CoreML
- Input: 16kHz mono WAV
- Output: Speaker segments with timestamps and IDs
Performance
| Dataset | DER | Speedup | Device |
|---|---|---|---|
| AMI (test) | TBD | 50x | iPhone 15 Pro |
| zant-echo-golden v1.0.0 | TBD | 50x | iPhone 15 Pro |
Usage
This model is consumed via the ZantAMI v0.1 contract.
Swift Integration
import FluidAudio
// Models are downloaded automatically via Swift Package Manager
let engine = ProductionDiarizationEngine.shared
await engine.initialize()
let result = try await engine.diarize(audioURL: url)
// Returns: [SpeakerSegment(start: 0.0, end: 5.3, speaker: "You", confidence: 0.85)]
Model Architecture
FluidAudio uses:
- Segmentation: Voice Activity Detection
- Embedding: WeSpeaker model (256-dimensional)
- Clustering: Hierarchical clustering with cosine similarity
License
MIT License
- Created
- Oct 2, 2025
- Updated
- Oct 2, 2025