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# parakeet-rs
[](https://github.com/altunenes/parakeet-rs/actions/workflows/rust.yml)
[](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<f32>, 16kHz mono, normalized)
let audio: Vec<f32> = /* 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.
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