--- license: mit library_name: coreml pipeline_tag: audio-to-audio tags: - coreml - core-ml - ios - macos - apple - on-device - voice-conversion - voice-cloning - arxiv:2312.01479 --- # OpenVoice V2 — Core ML *Voice Cloning* Zero-shot voice conversion. Clone a speaker from ~10s reference audio.

OpenVoice V2 demo

Core ML conversion of [myshell-ai/OpenVoice](https://github.com/myshell-ai/OpenVoice) for on-device inference on iPhone, iPad and Mac. Converted with `coremltools`; the packages are stateless, so all sequencing and buffering lives in your Swift code. | | | |---|---| | Task | audio to audio | | Upstream | [myshell-ai/OpenVoice](https://github.com/myshell-ai/OpenVoice) | | Packages | 2 | | Download size | 58 MB | | Minimum iOS | 17.0 | | Peak RAM | ~500 MB | ## Files | File | Size | Compute units | SHA-256 | |---|---:|---|---| | `OpenVoice_SpeakerEncoder.mlpackage.zip` | 1 MB | `cpuAndGPU` | `c3f2a96aaf5ecb5c…` | | `OpenVoice_VoiceConverter.mlpackage.zip` | 57 MB | `cpuAndGPU` | `ef3ce8a2d1564aef…` | | **Total** | **58 MB** | | | `compute_units` is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU. ## Download ```bash hf download mlboydaisuke/coreml-zoo --include "openvoice/*" --local-dir ./openvoice unzip './openvoice/openvoice/*.zip' -d ./openvoice ``` ## Use in Swift ```swift import CoreML let config = MLModelConfiguration() config.computeUnits = .cpuAndGPU // as converted — see the table above // Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it // at build time: let model = try OpenVoice_SpeakerEncoder(configuration: config) // ...or compile a downloaded .mlpackage at runtime: let compiled = try await MLModel.compileModel(at: mlpackageURL) let model = try MLModel(contentsOf: compiled, configuration: config) ``` > This model is split into 2 Core ML packages that are driven in sequence from Swift. Load them one at a time, copy the outputs out of the `MLMultiArray` buffers and release each model before loading the next — two large Core ML models resident at once will OOM on an iPhone. ## Demo - **Sample app** — [`sample_apps/OpenVoiceDemo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/OpenVoiceDemo), a standalone SwiftUI project. - **Models Zoo** — this model is downloadable and runnable inside the [Models Zoo app](https://apps.apple.com/app/id6762083207) on the App Store, no build required. ## Conversion - Script: [`convert_openvoice.py`](https://github.com/john-rocky/CoreML-Models/blob/master/conversion_scripts/convert_openvoice.py) - Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling): [`docs/coreml_conversion_notes.md`](https://github.com/john-rocky/CoreML-Models/blob/master/docs/coreml_conversion_notes.md) - Model index: [CoreML-Models](https://github.com/john-rocky/CoreML-Models) ## License The conversion inherits the upstream license: **MIT**. ## Credits - Upstream authors: [myshell-ai/OpenVoice](https://github.com/myshell-ai/OpenVoice), 2023 - Core ML conversion: john-rocky (Daisuke Majima)