# FluidInference/FluidAudio

Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.

Repository: https://github.com/FluidInference/FluidAudio
Canonical: https://ross.abutalabs.com/products/fluidaudio
Homepage: https://docs.fluidinference.com/introduction
Language: Swift
License: Apache-2.0
License Family: permissive
Topics: coreml, ios, macos, speaker-diarization, speaker-embedding, speaker-identification, speaker-recognition, swift, audio, avfoundation, real-time, vad, voice-activity-detection, asr, automatic-speech-recognition, speech-to-text, parakeet, ane, nvidia
Last push: 2026-08-23T00:04:40+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 86, longevity 31
- inputs: {"age_days": 438, "days_push": 11, "days_rel": 14, "gap_med": 3.5, "n_releases_24m": 63}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2699, forks 389 (observed 2026-08-28T04:07:11.253821+00:00)

## What it is
A Swift SDK providing fully local, low-latency audio AI on Apple devices, including speech-to-text (Parakeet), speaker diarization (Pyannote/Sortformer), voice activity detection (Silero), and text-to-speech (Kokoro) via CoreML models. Inference is offloaded to the Apple Neural Engine to minimize CPU/GPU usage, with integrations for Swift Package Manager, CocoaPods, React Native, and Rust/Tauri.

## Use cases
- transcribe audio recordings to text on-device
- add live streaming captions while the user speaks
- identify who spoke when in meeting recordings
- detect speech segments and skip silence before ASR
- convert text to speech locally with multiple voices
- recognize known speakers from pre-loaded voice profiles
- build an always-on voice assistant on macOS or iOS

## When to choose
- you need private, fully local audio AI on Apple devices without cloud APIs
- you want low-latency ASR, diarization, VAD, or TTS running on the Apple Neural Engine
- you're building a Swift/iOS/macOS app and want a few-lines-of-code integration
- you need streaming transcription or real-time speaker labels

## When to avoid
- you target Android, Windows, or Linux — this SDK is Apple-platform only
- you need server-side or GPU-cluster inference rather than on-device
- you need languages outside the 25 supported European languages for transcription
- you need more than 4 speakers in streaming diarization (Sortformer limit)

## Facets
- artifact type: library
- maturity: active
- function: speech-recognition, tts, audio-processing, machine-learning, sdk
- domain: speech-processing, machine-learning, apple-ecosystem, cross-platform
- platform: -
- tags: coreml, apple-neural-engine, speaker-diarization, voice-activity-detection, parakeet, pyannote, silero-vad, kokoro-tts, on-device-ai, swift-package-manager, audio, macos, ios, swift, gpu

## Member repositories
- FluidInference/FluidAudio (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:11.253821+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:16:06.846448+00:00, confidence not recorded.
  - readme: https://github.com/FluidInference/FluidAudio (fetched 2026-08-28T04:07:11.253821+00:00, sha 2ab71438f91b)
  - homepage: https://docs.fluidinference.com/introduction (fetched 2026-08-29T09:59:14.491188+00:00, sha ba9663dfb259)
  - site_page: https://docs.fluidinference.com/quickstart (fetched 2026-08-29T09:59:14.493860+00:00, sha 446d02ad2474)
  - site_page: https://docs.fluidinference.com/installation (fetched 2026-08-29T09:59:14.495598+00:00, sha 91bd550ec1d1)
  - site_page: https://docs.fluidinference.com/asr/getting-started (fetched 2026-08-29T09:59:14.497215+00:00, sha 630cbe6c1bb8)
  - site_page: https://docs.fluidinference.com/diarization/getting-started (fetched 2026-08-29T09:59:14.499177+00:00, sha 4f1f21e06546)
  - site_page: https://docs.fluidinference.com/vad/getting-started (fetched 2026-08-29T09:59:14.501081+00:00, sha 89bb9d7a4ff8)
  - site_page: https://docs.fluidinference.com/mobius/getting-started (fetched 2026-08-29T09:59:14.502757+00:00, sha a51c7e2356d5)
- Data as of 2026-08-30T08:39:29.467469+00:00.