whisper_ggml 2.4.0

OpenAI Whisper ASR (Automatic Speech Recognition) for Flutter

2.4.0

• Added transcription progress reporting (#6): transcribe (controller and low-level API) takes an optional onProgress callback invoked with whisper.cpp's inference progress as a 0–100 percentage (coarse steps). Implemented via a NativeCallable.listener handed to whisper_full_params.progress_callback, so events arrive on the calling isolate without blocking inference

2.3.0

• WhisperController.transcribe now exposes withSegments and splitOnWord (#14): pass withSegments: true to get per-segment timestamps in result.transcription.segments (fromTs/toTs as Duration), and add splitOnWord: true for one segment per word. Previously segments were only reachable through the low-level Whisper.transcribe API
• The diarize parameter now actually does something (#13): it enables whisper.cpp's tinydiarize speaker-turn detection. Use the new WhisperModel.smallEnTdrz model (English only) together with diarize: true and withSegments: true — segments after which the speaker changes carry speakerTurnNext == true. With regular (non-tdrz) models the flag remains a no-op, as it silently was since 1.7.0

2.2.0

• Added Linux support (x64): the vendored whisper.cpp v1.9.1 builds into libwhisper_ggml.so through the standard Flutter Linux CMake toolchain — both one-shot (transcribe) and live (transcribeLive) transcription work
• Removed the stale prebuilt libggml*.so binaries from linux/ — leftovers that never constituted a working implementation (no whisper code, wrong bundling variable) and only inflated the package
• Like Windows, Linux x64 targets AVX2 by default (-DWHISPER_GGML_AVX2=OFF for baseline SSE2) and uses an ffmpeg executable from PATH for non-WAV input
• Example app: added the Linux runner; the Record button captures 16 kHz WAV directly on Linux
• Fixed a native crash (SIGSEGV) on all platforms when the model file is missing or corrupt: transcribe called whisper_full with a null context instead of returning an error response (found by the new Linux test suite)
• Fixed a native memory leak on all platforms: error paths in transcribe (unreadable/wrong-format WAV, failed inference) returned without freeing the loaded model — ~150 MB leaked per failed call with the base model

2.1.0

• Added Windows support (x64): the vendored whisper.cpp v1.9.1 now also builds into whisper_ggml.dll through the standard Flutter Windows CMake toolchain — both one-shot (transcribe) and live (transcribeLive) transcription work
• Windows builds target AVX2 by default (matching upstream whisper.cpp's standard x64 binaries); pass -DWHISPER_GGML_AVX2=OFF to the plugin CMake for a baseline SSE2 build
• Audio conversion on Windows uses an ffmpeg executable from PATH when available (ffmpeg_kit has no Windows implementation); without it, input must already be 16 kHz mono WAV
• Native inference stays optimized (/O2) in Windows debug builds, matching the iOS/macOS behaviour
• Example app: added the Windows runner; the Record button captures 16 kHz WAV directly on Windows so no ffmpeg is needed

2.0.0

• Upgraded the vendored whisper.cpp from a 2023-era snapshot to v1.9.1 — roughly 15× faster transcription (an 11-second clip takes ~0.4 s with the base model on Apple Silicon), with Accelerate enabled on iOS/macOS
• The model-loading code that crashed on some physical iPhones was rewritten upstream (#22); verified working on the iOS simulator
• Removed the -march=armv8.2-a+fp16 Android compile flags that caused SIGILL crashes on armv8.0 devices (#15)
• Native code now compiles with -O3 in debug builds on iOS/macOS, so development-time transcription is no longer unusably slow
• Rewrote the README
• Note: while the Dart API is unchanged, the native engine swap is significant — hence the major version bump

1.9.2

• Removed the windows and linux platform declarations — neither has a native whisper implementation, and pub.dev advertised support that failed at runtime. Unsupported platforms now throw a clear UnsupportedError (#20)
• Ship consumer ProGuard rules so Android release builds no longer strip the bundled ffmpeg-kit classes, which broke plugin registration and surfaced as channel-error on unrelated plugins like path_provider (#16)

1.9.1

• Fixed a native crash (SIGABRT) when whisper emits text containing invalid UTF-8 — e.g. a token boundary splitting a multi-byte character, common with non-English audio. Invalid bytes are now replaced with U+FFFD instead of aborting the app (#21)

1.9.0

• Added live (streaming) transcription: WhisperController.transcribeLive takes a stream of 16 kHz mono PCM16 audio and returns a WhisperLiveSession that emits progressively refined partial transcripts while the user speaks; stop() returns the final text
• Live sessions load the model once and keep it in memory (new native stream_start / stream_feed / stream_stop API on Android, iOS, and macOS); inference runs on a dedicated isolate and never blocks the UI
• Adaptive energy gate keeps silence — digital or room tone — away from the decoder, preventing [BLANK_AUDIO] markers and hallucinated repetition; tunable per session via gateRmsMin, gateVoiceRatio, and gateNoiseFloorCap
• Added suppressNonSpeechTokens parameter (whisper_full_params.suppress_non_speech_tokens) to TranscribeRequest, transcribe, and transcribeLive
• Fixed a native memory leak: FFI response buffers were never freed — one small leak per one-shot transcription, unbounded growth for streaming
• Example app: redesigned UI with dedicated Live and Record microphone buttons and a JFK sample button; live transcripts update on screen while speaking
• Fixed macOS example: added the missing microphone entitlement

1.8.0

• Added initialPrompt parameter to TranscribeRequest and WhisperController.transcribe
• Wired initial_prompt through to whisper_full_params.initial_prompt on Android, iOS, and macOS to bias decoding toward domain-specific vocabulary, names, and punctuation
• Added noContext parameter (whisper_full_params.no_context, equivalent to Python whisper's condition_on_previous_text=False) on Android, iOS, and macOS to disable cross-segment text conditioning — helps against hallucinated repetition on short utterances
• Empty / null prompt and noContext: false leave whisper.cpp defaults, so existing callers see no behaviour change
• Removed unused flutter_riverpod dependency, which was constraining consumers to riverpod 2.x even though the package never imported it
• Fixed example app crash on macOS when transcribing the bundled jfk.wav (temporary directory did not exist)

1.7.0

• Connected diarize transcribe parameter to the underlying whisper C++ code
• Added diarize parameter to the transcribe method

1.6.0

• Fixed iOS issues
• Added auto language support for iOS
• Fixed example project
• Increased NDK version in order to support Google 16 KB requirement

1.5.0

• Switched main FFmpeg from heavy ffmpeg_kit_flutter_new: ^1.6.1 to lightweight ffmpeg_kit_flutter_new_min: ^2.1.0
• Upgraded recorder dependency for example project from v5.2.1 to v6.0.0
• Updated main code files

1.4.0

• Added ability to use "auto" language detection
• Upgraded pubspec.yaml dependencies

1.3.0

• Upgraded Android bindings to work with Flutter 3.29
• Added new FFmpeg kit dependency

1.2.0

• Fixed Android v1 embedding issue by adding override for ffmpeg_kit_flutter_full_gpl
• Upgraded dependencies

1.1.1

• Cleaned up code

1.1.0

• Added support for MacOS

1.0.0

• Added support for Android and iOS