Changelog

All notable user-facing changes to Moonshine Voice are documented in this file.

The format is based on Keep a Changelog.

[0.1.1] - August 6th, 2026

Speculative decoding for streaming speech-to-text, on by default. Streaming re-decodes verify the previous hypothesis and continue from the first mismatch instead of restarting from BOS, cutting live latency on several platforms (for example Medium Streaming on MacBook Pro from ~103ms to ~74ms). Disable with use_speculative_decoding=false.
AgentFlow.otherwise() — a callback for speech that matched no trigger and no waiting prompt, so dictation-style UIs can take free-form lines without treating them as failed commands.
Cross-platform voice cloning API: cloning(), clone_from(), and start_cloning() / VoiceClone for file, PCM, or live microphone capture, aligned across Python, JavaScript, Swift, and Java.
AgentFlow and voice-cloning examples on Android and iOS/Swift, plus dictation and meeting note taker web examples.
Language tabs on the web example code snippets.
Hugging Face mirror of every downloadable asset at moonshine-ai/moonshine-voice-assets.

Breaking: DialogFlow is renamed to AgentFlow everywhere (APIs, packages, and example apps).
Breaking: High-level client APIs are regularized across Python, JavaScript, Swift, and Java around construct → configure with chainable setters → load(). In particular, Python MicTranscriber and TextToSpeech no longer download and open models inside the constructor.
Breaking: The C++ binding (moonshine-cpp.h) follows the same higher-level shape for transcription and TTS.
Breaking: Only OnnxRuntime flatbuffer models (.ort) are accepted. Supplying .onnx (or ONNX external-data sidecars) fails with a clear migration error. Convert with python scripts/convert-models-to-ort.py. See docs/ort-only-models.md.
Breaking: Speaker-diarization models are no longer embedded in the library. With identify_speakers, they download on first use like other models (~8 MB off every mobile binary; Android arm64 install ~24.6 MB → ~16.4 MB, iOS linked binary ~30.6 MB → ~22.4 MB). See docs/diarization-models.md.
Downloadable assets are served from download.moonshine.ai (and the Hugging Face mirror) instead of the old GCP-hosted buckets; large model blobs are no longer kept in git LFS in this repo.
Smaller WebAssembly downloads after ORT-only packaging and cleanup of unused model files.
Improved quantization accuracy for shipped models.
Streaming transcription backs off the inference interval when it falls behind realtime, to reduce piled-up work.

Remaining public references to the old Intent API (use AgentFlow phrase matching instead).
Embedded diarization model payloads from the core library binary.