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diff --git a/parakeet-rs/README.md b/parakeet-rs/README.md deleted file mode 100644 index 75dfe85..0000000 --- a/parakeet-rs/README.md +++ /dev/null @@ -1,122 +0,0 @@ -# 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. |