parakeet-rs

Fast English speech recognition with NVIDIA's Parakeet model via ONNX Runtime. Note: CoreML doesn't work 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! :-)

use parakeet_rs::Parakeet;

let mut parakeet = Parakeet::from_pretrained(".")?;
let result = parakeet.transcribe("audio.wav")?;
println!("{}", result.text);

// Token-level timestamps
for token in result.tokens {
    println!("[{:.3}s - {:.3}s] {}", token.start, token.end, token.text);
}

Setup

Download from HuggingFace: model.onnx, model.onnx_data, tokenizer.json

Quantized versions also available (fp16, int8, q4). All 3 files must be in the same directory.

GPU support:

parakeet-rs = { version = "0.x", features = ["cuda"] }

use parakeet_rs::{ExecutionConfig, ExecutionProvider};

let config = ExecutionConfig::new().with_execution_provider(ExecutionProvider::Cuda);
let mut parakeet = Parakeet::from_pretrained_with_config(".", config)?;

Features

• English transcription with punctuation & capitalization
• Token-level timestamps from CTC output
• Batch processing: transcribe_batch(&["a.wav", "b.wav"]) etc
• See examples/pyannote.rs for speaker diarization + transcription.

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.