parakeet-rs 0.2.3

# parakeet-rs
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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 (Speaker Diarization)**: NVIDIA's 4-speaker diarization

Enable the feature:
```toml
parakeet-rs = { version = "0.2", features = ["sortformer"] }
```

```rust
#[cfg(feature = "sortformer")]
use parakeet_rs::sortformer::Sortformer;
let audio: Vec<f32> = 
// Perform diarization
let mut sortformer = Sortformer::new("diar_sortformer_4spk-v1.onnx")?;
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**: Download from [HuggingFace](https://huggingface.co/altunenes/parakeet-rs/blob/main/diar_sortformer_4spk-v1.onnx): `diar_sortformer_4spk-v1.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: Speaker diarization (up to 4 speakers)](https://huggingface.co/altunenes/parakeet-rs/blob/main/diar_sortformer_4spk-v1.onnx)
- 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.