# parakeet-rs [![Rust](https://github.com/altunenes/parakeet-rs/actions/workflows/rust.yml/badge.svg)](https://github.com/altunenes/parakeet-rs/actions/workflows/rust.yml) [![crates.io](https://img.shields.io/crates/v/parakeet-rs.svg)](https://crates.io/crates/parakeet-rs) Fast speech recognition with NVIDIA's Parakeet models via ONNX Runtime. Note: CoreML doesn't stable with this model - stick w/ CPU (or other GPU EP like CUDA). But its incredible fast in my Mac M3 16gb' CPU compared to Whisper metal! :-) ## Models **CTC (English-only)**: Fast & accurate ```rust use parakeet_rs::Parakeet; let mut parakeet = Parakeet::from_pretrained(".", None)?; let result = parakeet.transcribe_file("audio.wav")?; println!("{}", result.text); // Or transcribe in-memory audio // let result = parakeet.transcribe_samples(audio, 16000, 1)?; // Token-level timestamps for token in result.tokens { println!("[{:.3}s - {:.3}s] {}", token.start, token.end, token.text); } ``` **TDT (Multilingual)**: 25 languages with auto-detection ```rust use parakeet_rs::ParakeetTDT; let mut parakeet = ParakeetTDT::from_pretrained("./tdt", None)?; let result = parakeet.transcribe_file("audio.wav")?; println!("{}", result.text); // Or transcribe in-memory audio // let result = parakeet.transcribe_samples(audio, 16000, 1)?; // Token-level timestamps for token in result.tokens { println!("[{:.3}s - {:.3}s] {}", token.start, token.end, token.text); } ``` **EOU (Streaming)**: Real-time ASR with end-of-utterance detection ```rust use parakeet_rs::ParakeetEOU; let mut parakeet = ParakeetEOU::from_pretrained("./eou", None)?; // Prepare your audio (Vec, 16kHz mono, normalized) let audio: Vec = /* your audio samples */; // Process in 160ms chunks for streaming const CHUNK_SIZE: usize = 2560; // 160ms at 16kHz for chunk in audio.chunks(CHUNK_SIZE) { let text = parakeet.transcribe(chunk, false)?; print!("{}", text); } ``` **Sortformer v2 (Speaker Diarization)**: Streaming 4-speaker diarization ```toml parakeet-rs = { version = "0.2", features = ["sortformer"] } ``` ```rust use parakeet_rs::sortformer::{Sortformer, DiarizationConfig}; let mut sortformer = Sortformer::with_config( "diar_streaming_sortformer_4spk-v2.onnx", None, DiarizationConfig::callhome(), // or dihard3(),custom() )?; let segments = sortformer.diarize(audio, 16000, 1)?; for seg in segments { println!("Speaker {} [{:.2}s - {:.2}s]", seg.speaker_id, seg.start, seg.end); } ``` See `examples/diarization.rs` for combining with TDT transcription. ## Setup **CTC**: Download from [HuggingFace](https://huggingface.co/onnx-community/parakeet-ctc-0.6b-ONNX/tree/main/onnx): `model.onnx`, `model.onnx_data`, `tokenizer.json` **TDT**: Download from [HuggingFace](https://huggingface.co/istupakov/parakeet-tdt-0.6b-v3-onnx): `encoder-model.onnx`, `encoder-model.onnx.data`, `decoder_joint-model.onnx`, `vocab.txt` **EOU**: Download from [HuggingFace](https://huggingface.co/altunenes/parakeet-rs/tree/main/realtime_eou_120m-v1-onnx): `encoder.onnx`, `decoder_joint.onnx`, `tokenizer.json` **Diarization (Sortformer v2)**: Download from [HuggingFace](https://huggingface.co/altunenes/parakeet-rs/blob/main/diar_streaming_sortformer_4spk-v2.onnx): `diar_streaming_sortformer_4spk-v2.onnx` Quantized versions available (int8). All files must be in the same directory. GPU support (auto-falls back to CPU if fails): ```toml parakeet-rs = { version = "0.1", features = ["cuda"] } # or tensorrt, webgpu, directml, rocm ``` ```rust use parakeet_rs::{Parakeet, ExecutionConfig, ExecutionProvider}; let config = ExecutionConfig::new().with_execution_provider(ExecutionProvider::Cuda); let mut parakeet = Parakeet::from_pretrained(".", Some(config))?; ``` ## Features - [CTC: English with punctuation & capitalization](https://huggingface.co/nvidia/parakeet-ctc-0.6b) - [TDT: Multilingual (auto lang detection) ](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3) - [EOU: Streaming ASR with end-of-utterance detection](https://huggingface.co/nvidia/parakeet_realtime_eou_120m-v1) - [Sortformer v2: Streaming speaker diarization (up to 4 speakers)](https://huggingface.co/nvidia/diar_streaming_sortformer_4spk-v2) - Token-level timestamps (CTC, TDT) ## Notes - Audio: 16kHz mono WAV (16-bit PCM or 32-bit float) ## License Code: MIT OR Apache-2.0 FYI: The Parakeet ONNX models (downloaded separately from HuggingFace) are licensed under **CC-BY-4.0** by NVIDIA. This library does not distribute the models.