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Runs in the browser (WebAssembly + LiteRT.js) and server-side in Node (native), from one import.","maintainers":[{"name":"finnvoorhees","email":"finn@detail.co"},{"name":"laurierrochon","email":"laurier@detail.co"},{"name":"pveugen","email":"paul@pave4.com"},{"name":"akagabi","email":"gabesuit@gmail.com"}],"readme":"# @desert-ant-labs/clear\n\nOn-device speech enhancement for JavaScript. Takes a noisy mono recording\n(laptop mic, untreated room, traffic) and returns podcast-ready 48 kHz audio:\ndenoise and dereverb from a fine-tuned [DeepFilterNet 3][dfn], then loudness\nnormalization to a delivery target. Everything runs locally, so the audio never\nleaves the device or browser.\n\n[dfn]: https://github.com/Rikorose/DeepFilterNet\n\nTwo entries share one `Clear` API:\n\n- **`@desert-ant-labs/clear`** (default): a WebAssembly pipeline with\n  [LiteRT.js](https://www.npmjs.com/package/@litertjs/core) inference\n  (XNNPACK-accelerated CPU by default, optional WebGPU), for the **browser**. It\n  has no native dependencies, so a single import builds cleanly for every target\n  of a multi-target bundler (Next.js, Remix, SvelteKit, Nuxt), including the\n  browser bundle and the Client-Component SSR pass those frameworks render in\n  Node. It is safe to *import* during server-side rendering, but LiteRT.js needs\n  a browser (or Web Worker) to initialize, so `Clear.load()` runs inference only\n  in the browser; calling it in plain Node throws an actionable error pointing\n  you to `/native`.\n- **`@desert-ant-labs/clear/native`**: a prebuilt native core (LiteRT on Linux,\n  Core ML on macOS), for **server-side inference** in Node. No `@litertjs/core`,\n  no build tools, no flags. Import it from server-only code (API routes, server\n  actions, plain Node scripts). Do not import it from a component that also\n  renders in the browser.\n\n```bash\n# Browser (default entry):\nnpm i @desert-ant-labs/clear @litertjs/core\n\n# Server-side inference in Node (/native entry) needs no extra install:\nnpm i @desert-ant-labs/clear\n```\n\n## Usage\n\n```ts\nimport { Clear } from \"@desert-ant-labs/clear\";           // browser\n// import { Clear } from \"@desert-ant-labs/clear/native\"; // server-side Node\n\nconst clear = await Clear.load();          // downloads and caches on first use\nconst result = await clear.enhance(samples, 48_000);\n\nresult.samples;                // Float32Array, 48 kHz mono, whatever went in\nresult.measuredLUFS;           // integrated loudness of the input\nresult.measuredTruePeakDBFS;   // true peak of the output, after limiting\nresult.realtimeFactor;         // above 1 is faster than real time\n\nclear.dispose();\n```\n\nInput can be a `Float32Array` or a plain array of numbers, at any sample rate.\n\n## Channels\n\nThe output is **mono by default**, whatever goes in - the model is mono, so\nkeeping a stereo pair costs an inference pass per channel (about 1.8x a mono\nrun). Pass one entry per channel *and* ask to keep them:\n\n```ts\nconst stereo = await clear.enhance([left, right], 48_000, { channelMode: \"preserve\" });\nstereo.channelCount;   // 2\nstereo.channels;       // [Float32Array, Float32Array]\nstereo.samples;        // the first channel\n```\n\nLeaving `channelMode` alone (or setting it to `\"mono\"`) downmixes before\nenhancement, so the model runs once:\n\n```ts\nawait clear.enhance([left, right], 48_000);   // one channel out, one inference pass\n```\n\nMastering is joint: one loudness gain and one limiter envelope across the\nchannels, so it never moves the stereo image. `balanceChannelsLUFS` is the\ndeliberate exception, for a pair whose sides were recorded at different levels:\n\n```ts\nawait clear.enhance([left, right], 48_000,\n                    { channelMode: \"preserve\", balanceChannelsLUFS: -20 });\n```\n\n## Mastering\n\nBy default the output is normalized to the Apple Podcasts target (-19 LUFS) with\na -1.5 dBTP ceiling, held by a look-ahead limiter rather than by turning the\nwhole file down to fit its loudest transient.\n\n```ts\nawait clear.enhance(samples, 48_000, { targetLUFS: \"spotify\" });   // -14 LUFS\nawait clear.enhance(samples, 48_000, { targetLUFS: -23 });         // an explicit target\nawait clear.enhance(samples, 48_000, { targetLUFS: null });        // skip mastering\n```\n\n`LOUDNESS_PRESETS` carries the published platform targets (`applePodcasts`,\n`spotify`, `youtube`, `broadcast`). Two more knobs are available:\n`peakCeilingDBFS` (default -1.5) and `maxGainDB` (default 9), which bounds how\nfar a very quiet input is lifted so the model's noise floor does not come up\nwith it.\n\n`strength` blends the enhanced signal against the original, for when full\ndenoising sounds too processed:\n\n```ts\nawait clear.enhance(samples, 48_000, { strength: 0.7 });\n```\n\n`outputSampleRate` sets the delivery rate. The model always runs at 48 kHz and\nthe result is resampled on the way out, so the meter and the limiter still see\nthe rate their constants are derived for:\n\n```ts\nawait clear.enhance(samples, 48_000, { outputSampleRate: 44_100 });\n```\n\n## Self-hosting and progress\n\n```ts\nconst clear = await Clear.load({\n  modelBaseUrl: \"/assets/clear/\",     // browser: serve the files yourself\n  directory: \"/var/cache/clear\",      // Node: adopt or download here\n  onProgress: (fraction) => console.log(fraction),\n});\n```\n\nThe model repo and revision are pinned to this SDK version, so an install is\nreproducible. Weights live on [Hugging\nFace](https://huggingface.co/desert-ant-labs/clear).\n\n## License\n\nSee [LICENSE.md](./LICENSE.md).\n","readmeFilename":"README.md"}