Building an offline speech-to-text app with Flutter, FFI, whisper.cpp and FFmpeg

Описание и применение

Приложение Extracter позволяет преобразовывать любые аудио‑ и видеофайлы в текст полностью на устройстве, без загрузки в облако, используя Flutter, FFmpeg и whisper.cpp.

Задача

Transcribing audio or video locally without uploading to cloud services.

Результат

Extracter delivers line‑by‑line transcripts for any audio/video file on Android, iOS, and macOS, with no network usage after model download.

Рабочий процесс

• Select audio/video file
• FFmpeg decodes to 16 kHz mono PCM
• Whisper.cpp processes 30‑second windows fed in ~3‑minute chunks
• Native FFI plugin posts events (progress, segment, logs, DONE) to Dart
• Flutter UI streams segments line‑by‑line
• User can view history, export to TXT/SRT/VTT, or copy text

Доказательства

Cloud transcription is convenient until you have a recording you'd rather not upload: a lecture, a client call, a voice note.

Источник

Extracter, an open‑source Flutter app that turns any audio or video file into text entirely on the device.

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The heavy lifting lives in a small FFI plugin, extracter_native, with one C ABI shared by every platform:

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The app crashed with SIGSEGV, and the backtrace pointed at the line where the worker called the callback.

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Posting to the port of a dead isolate just returns false, so nothing crashes.

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