aufklarer/Parakeet-TDT-v3-CoreML-INT4

Parakeet TDT v3 — CoreML INT4

CoreML conversion of NVIDIA Parakeet-TDT 0.6B v2 with INT4-quantized encoder for Apple Neural Engine acceleration.

Models

Model	Description	Compute	Quantization
encoder.mlmodelc	FastConformer encoder (24L, 1024 hidden)	CPU + Neural Engine	INT4 palettized
decoder.mlmodelc	LSTM prediction network (2L, 640 hidden)	CPU + Neural Engine	FP16
joint.mlmodelc	TDT dual-head joint (token + duration logits)	CPU + Neural Engine	FP16

Additional Files

File	Description
vocab.json	SentencePiece vocabulary (1024 tokens)
config.json	Model configuration

Notes

• Mel preprocessing is done in Swift using Accelerate/vDSP (not CoreML) because torch.stft tracing bakes audio length as a constant, breaking per-feature normalization for variable-length inputs.
• Encoder uses EnumeratedShapes (100–3000 mel frames, covering 1–30s audio) to avoid BNNS crashes with dynamic shapes.
• Performance: ~110x RTF on M4 Pro via Neural Engine.

Usage

Used by qwen3-asr-swift ParakeetASR module:

let model = try await ParakeetASRModel.fromPretrained()
let text = try model.transcribeAudio(samples, sampleRate: 16000)