Changelog

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0.5.0 - 2026-05-20

Initial public release. Native Elixir Whisper speech-to-text backed by CTranslate2 through a Rustler NIF over ct2rs::sys::Whisper. No Python.

Features

  • WhisperCt2.load_model/2 loads a CTranslate2-converted Whisper model directory and returns a %WhisperCt2.Model{} with resolved :device and :compute_type.
  • WhisperCt2.transcribe/3 accepts {:pcm_f32, binary} (mono, 16 kHz, little-endian f32) and returns a %WhisperCt2.Transcription{} whose :segments carry absolute start/end times, :no_speech_prob, :avg_logprob, the underlying token IDs, and optional per-word timing.
  • WhisperCt2.transcribe_batch/3 stacks every chunk of every input into one encoder forward pass - a large speedup for diarization-driven workflows with many short turns.
  • :initial_prompt and :prefix bias decoding; :word_timestamps adds a batched DTW alignment pass attaching %WhisperCt2.Word{} entries; :with_timestamps toggles <|t_..|> segment timestamps for plain-text fine-tunes.
  • English-only checkpoints (*.en) use the [<|startoftranscript|>] prompt; multilingual checkpoints use [sot, lang, transcribe].
  • WhisperCt2.Pcm.slice/4 carves sub-windows out of an already-decoded f32 buffer with loud bounds checking.
  • WhisperCt2.available_devices/0 reports CPU/CUDA device counts and the build's CUDA-support flag.
  • Structured %WhisperCt2.Error{} taxonomy: :invalid_request, :load_error, :inference_error, :runtime_error, :nif_panic, :native_error.

Backends

  • Precompiled NIF artefacts via rustler_precompiled for aarch64-apple-darwin (Accelerate), x86_64-unknown-linux-gnu (oneDNN, optional mkl variant), and aarch64-unknown-linux-gnu (oneDNN). CUDA is loaded lazily via cuda-dynamic on every Linux artefact, so one binary runs on CPU-only and CUDA hosts alike.
  • Opt into a source build with WHISPER_CT2_BUILD=1, or pick the MKL artefact on x86_64 Linux with WHISPER_CT2_VARIANT=mkl.