clear

Sound

Delivers a rich, present, close-miked podcast sound.

• Denoised. HVAC, keyboard clicks, mouse rustle, mic bumps, room hum, laptop fans, coffee shop background, all pulled down without chewing consonants.
• Dereverbed. Untreated bedrooms, offices and hotel rooms come out sounding closer to a treated studio. The model does not add reverberation of its own.
• Warm and present. Low-mids brought forward so voice sits comfortably in a mix rather than sounding thin or distant.
• Sibilance-safe. No harsh peaks introduced when cleaning up S / T / F consonants.
• No pumping or musical-noise artefacts. Breaths, plosives and vocal texture stay intact.

Variants

Two variants ship. They take the same input, produce the same output format and cost the same to run, so switching between them is a one-line change in the SDK. Pick by the sound you want, not by platform: both ship for every runtime.

clear-studio

The default. Quiet, studio-like character; silences sit close to true zero.

Best for solo podcasts, tutorials, voiceover, video demos, screen recordings, and anything that wants a clean broadcast feel.

clear-natural

Preserves room tone, breath, and lip texture.

For treated podcast studios, intentional voiceover, interviews where the room is part of the take, and remote guest recordings where absolute silence would sound wrong.

Performance

The Core ML variants are optimized for the Apple Neural Engine. MLComputePlan confirms that all 492 model operations run on ANE.

clear-studio, whole SDK pipeline on a 60-second clip, best of three:

On iPhone 16 Pro, first-ever model loading takes approximately 3.4 seconds while Core ML compiles the ANE program. Cached launches load in approximately 62ms; applications should warm the model in the background.

Core AI

clear-studio.aimodel and clear-natural.aimodel are Core AI builds for iOS 27 and macOS 27, with fp16 weights. On an iPhone 17 Pro the studio variant runs the whole SDK pipeline at 413x realtime, against 366x for the Core ML build on the same device and clip.

These files are provisional. The Core AI toolchain is in beta and its asset format has changed between beta releases, so both will be rebuilt against the released toolchain. No SDK resolves them yet.

Try it

Install

Swift (requirements)

.package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core.git", from: "3.1.0")

Then add the Clear product to your target.

Kotlin (requirements)

implementation("ai.desertant:clear:3.1.0")

JavaScript (requirements)

npm i @desert-ant-labs/clear @litertjs/core   # browser
npm i @desert-ant-labs/clear                  # Node, prebuilt native core

What it's good for

• Meeting recorders. Zoom, Teams, Meet, Detail exports, single or multi-speaker.
• Bluetooth microphones. AirPods, Sony, headset mics.
• Mobile devices. iPhone and Android built-in microphone recordings, voice notes, field recordings.
• Laptop built-in microphones. MacBook and PC built-in mics.
• Untreated rooms. Bedrooms, hotel rooms, kitchens, coffee shops.

Whenever the pitch is messy recording in, clean audio out.

What it is not

• Not a general-purpose audio denoiser. Speech is the target; music, effects, and non-vocal signals get pulled down as noise.
• Not a source separator. Overlapping speakers stay overlapping.
• Not a voice changer, cloner, or transcription model.

Keywords

speech enhancement · noise suppression · dereverberation · speech denoising · reduce noise · clean up audio · normalize volume · turn a recording into studio sound · messy recording in clean audio out · podcast audio · voice cleanup · meeting recorder cleanup · bluetooth microphone cleanup · mobile device audio · built-in microphone · on-device audio · edge ML · Core ML · ONNX · iOS speech enhancement · Android speech enhancement · real-time speech enhancement · studio sound · podcast sound · Apple Neural Engine · ANE

License

[Desert Ant Labs Source-Available License](https://license.des