crispasr

Python bindings for CrispASR — lightweight on-device speech recognition via ggml.

Supports the ASR backends compiled into the linked CrispASR library, including Whisper, Qwen3-ASR, FastConformer, Canary, Parakeet, Cohere, Granite-Speech, Voxtral, wav2vec2, GLM-ASR, Kyutai-STT, Moonshine, FireRed, OmniASR, and VibeVoice-ASR.

Install

pip install crispasr

This wheel is pure Python and does not bundle the native library — install libcrispasr separately, the same way crispasr's Python bindings work:

macOS

brew install crispasr        # once published; until then build from source

Linux / Windows / from source

git clone https://github.com/CrispStrobe/CrispASR
cd CrispASR
cmake -B build && cmake --build build -j
sudo cmake --install build   # installs libcrispasr.{so,dylib,dll}

If libcrispasr is in a non-standard location, set CRISPASR_LIB_PATH:

export CRISPASR_LIB_PATH=/path/to/libcrispasr.so

Quick start

from crispasr import CrispASR

model = CrispASR("ggml-base.en.bin")
for seg in model.transcribe("audio.wav"):
    print(f"[{seg.start:.1f}s - {seg.end:.1f}s] {seg.text}")
model.close()

Or use the unified Session API for non-Whisper backends (Qwen3-ASR, FastConformer, Parakeet, …):

from crispasr import Session

s = Session("qwen3-asr-0.6b-q4_k.gguf")
for seg in s.transcribe_pcm(pcm_f32, sample_rate=16000):
    print(seg.text)

API

• CrispASR — Whisper-compatible high-level API
• Session — unified API across all backends compiled into libcrispasr
• align_words(...) — word-level CTC alignment
• diarize_segments(...) — speaker diarization (energy / xcorr / vad-turns / pyannote)
• SpeakerEmbedder(spec) — pluggable embedder ("auto"/"titanet", "indextts"/"ecapa", or a .gguf path)
• PyannoteCache(pcm, model) — pre-computed pyannote-seg posteriors for cross-slice consistency
• agglomerative_cluster(embeddings, ...) — single-linkage cosine clustering for globally stable speaker IDs
• TitaNet / SpeakerDB — standalone speaker verification + closed-roster profile matching (consent-gated; requires expected_names + consent=True, see docs/diarization-speakers.md)
• detect_language_pcm(...) — language ID
• registry_lookup(...) — auto-download known models from the model hub
• registry_default_bundle(...) — enumerate the exact primary, companion, and extra files used by -m auto, including licence-acceptance policy

See the main repo for full documentation, model registry, and CLI.

License

MIT — see LICENSE.