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Silero Vad Coreml

A CoreML implementation of the Silero Voice Activity Detection (VAD) model, optimized for Apple platforms (iOS/macOS). This repository contains pre-converted CoreML models ready for use in Swift applications.

Typevoice-activity-detectionModèle de baseonnx-community/silero-vadVersionÉditeur@aoiandroidCClasse

Source du modèle

Type
voice-activity-detection
Taille du fichier
243 B
Modèle de base
onnx-community/silero-vad
Version
vcoremldata
Mis à jour
8 oct. 2026
Éditeur
@aoiandroid
Source
Hugging Face

Description de la source

** 🧃 CoreML Silero VAD **

Discord GitHub Repo stars

A CoreML implementation of the Silero Voice Activity Detection (VAD) model, optimized for Apple platforms (iOS/macOS). This repository contains pre-converted CoreML models ready for use in Swift applications.

See FluidAudio Repo link at the top for more information

Model Description

Developed by: Silero Team (original), converted by FluidAudio

Model type: Voice Activity Detection

License: MIT

Parent Model: silero-vad

This is how the model performs against the silero-vad v6.0.0 basline Pytorch JIT version

graphs/yc_standard_comparison_20250915_205721_2c04b81.png graphs/yc_256ms_comparison_20250915_205721_2c04b81.png

Note that we tested the quantized versions, as the model is already tiny, theres no performance imporvement at all.

This is how the different models compare in terms of speed, the 256s takes in 8 chunks of 32ms and processes it in batches so its much faster graphs/yc_performance_20250915_205721_2c04b81.png

Conversion code is available here: FluidInference/mobius

Intended Use

Primary Use Cases

  • Real-time voice activity detection in iOS/macOS applications
  • Speech preprocessing for ASR systems
  • Audio segmentation and filtering

How to Use

Citation

@misc{silero-vad-coreml, title={CoreML Silero VAD}, author={FluidAudio Team}, year={2024},

url={https://huggingface.co/alexwengg/coreml-silero-vad} }

@misc{silero-vad, title={Silero VAD}, author={Silero Team}, year={2021}, url={https://github.com/snakers4/silero-vad} }

Sources

1 source
Hugging FacePrincipalVersion a97cb2f2b2addbbdcc11df380bcccf9d0f3ddc11
huggingface.co/aoiandroid/silero-vad-coreml/tree/a97cb2f2b2addbbdcc11df380bcccf9d0f3ddc11

Vérifié 9 sept.

Artefacts du modèle

1 artefact

silero_vad_se_trained_4bit.mlmodelc/analytics/coremldata.bin

bin · 243 B · SHA-256 ed0b15a6463e…17a4 · Hugging Face

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Extraits de sources

3 extraits

--- license: mit tags: - audio - voice-activity-detection - coreml - silero - speech - ios - macos - swift library_name: coreml pipeline_tag: voice-activity-detection datasets: - alexwengg/musan_mini50 - alexwengg/musan_mini100 metrics: - accuracy - f1 language: - en base_model: - onnx-community/silero-vad --- # **<span style="color:#5DAF8D">🧃 CoreML Silero VAD </span>** [![Discord](https://img.shields.io/badge/Discord-Join%20Chat-7289da.svg)](https://discord.gg/WNsvaCtmDe) [![GitHub Repo stars](https://img.shields.io/github/stars/FluidInference/FluidAudio?style=flat&logo=github)](https://github.com/FluidInference/FluidAudio) A CoreML implementation of the Silero Voice Activity Detection (VAD) model, optimized for Apple platforms (iOS/macOS). This repository contains pre-converted CoreML models ready for use in Swift applications. See FluidAudio Repo link at the top for more information ## Model Description **Developed by:** Silero Team (original), converted by FluidAudio **Model type:** Voice Activity Detection **License:** MIT **Parent Model:** [silero-vad](https://github.com/snakers4/silero-vad) This is how the model performs against the silero-vad v6.0.0 basline Pytorch JIT version ![graphs/yc_standard_comparison_20250915_205721_2c04b81.png](graphs/yc_standard_comparison_20250915_205721_2c04b81.png) ![graphs/yc_256ms_comparison_20250915_205721_2c04b81.png](graphs/yc_256ms_comparison_20250915_205721_2c04b81.png) Note that we tested the quantized versions, as the model is already tiny, theres no performance imporvement at all. This is how the different models compare in terms of speed, the 256s takes in 8 chunks of 32ms and processes it in batches so its much faster ![graphs/yc_performance_20250915_205721_2c04b81.png](graphs/yc_performance_20250915_205721_2c04b81.png) Conversion code is available here: [FluidInference/mobius](https://github.com/FluidInference/mobius) ## Intended Use ### Primary Use Cases - Real-time voice activity detection in iOS/macOS applications - Speech preprocessing for ASR systems - Audio segmentation and filtering ## How to Use Citation @misc{silero-vad-coreml, title={CoreML Silero VAD}, author={FluidAudio Team}, year={2024}, url={https://huggingface.co/alexwengg/coreml-silero-vad} } @misc{silero-vad, title={Silero VAD}, author={Silero Team}, year={2021}, url={https://github.com/snakers4/silero-vad} }...

Source context: 18 downloads · 0 likes · Pipeline voice-activity-detection · Library coreml · Repo aoiandroid/silero-vad-coreml

Source context: 4 downloads · 0 likes · Pipeline voice-activity-detection · Library coreml · Repo aoiandroid/silero-vad-coreml