aoiandroid / parakeet-tdt-ja-coreml

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Model's Last Updated: June 21 2026
automatic-speech-recognition

Introduction of parakeet-tdt-ja-coreml

Model Details of parakeet-tdt-ja-coreml

Parakeet TDT Japanese CoreML Models

CoreML conversion of nvidia/parakeet-tdt_ctc-0.6b-ja for on-device Japanese speech recognition on Apple platforms (iOS/macOS).

Model Description

This is a CoreML conversion of NVIDIA's Parakeet TDT 0.6B Japanese model, a state-of-the-art automatic speech recognition (ASR) model based on the FastConformer-TDT (Token-and-Duration Transducer) architecture.

Key Features
  • Language : Japanese (ja)
  • Architecture : Hybrid FastConformer-TDT-CTC
  • Vocabulary Size : 3,072 tokens (SentencePiece BPE)
  • Sample Rate : 16 kHz
  • Fixed Audio Window : 15 seconds (240,000 samples)
Model Components
Component File Input Shape Output Shape
Preprocessor preprocessor.mlpackage [1, 240000] [1, 80, T]
Encoder encoder.mlpackage [1, 80, 1501] [1, 1024, 188]
Decoder decoder.mlpackage [1, 1] + LSTM states [1, 640, 2] + states
Joint joint.mlpackage encoder + decoder outputs [1, 188, 1, 3078]
Mel+Encoder (Fused) mel_encoder.mlpackage [1, 240000] [1, 1024, 188]
Vocabulary vocab_ja.json - 3,072 tokens
Usage
Swift Example
import CoreML

// Load models
let encoder = try MLModel(contentsOf: encoderURL)
let decoder = try MLModel(contentsOf: decoderURL)
let joint = try MLModel(contentsOf: jointURL)

// Or use the fused mel_encoder for simpler pipeline
let melEncoder = try MLModel(contentsOf: melEncoderURL)
Important Notes
  1. Fixed Input Shapes : Models use fixed shapes for stability. Audio must be padded/trimmed to 15 seconds (240,000 samples at 16kHz).

  2. Encoder Output Format : Japanese model outputs (B, features, time) = (1, 1024, T) , different from English v3 models which output (B, T, features) .

  3. Greedy Decoding : Use standard TDT greedy decoding with the decoder and joint networks.

Technical Specifications
{
  "model_id": "nvidia/parakeet-tdt_ctc-0.6b-ja",
  "vocab_size": 3072,
  "hidden_size": 640,
  "encoder_features": 1024,
  "num_decoder_layers": 2,
  "sample_rate": 16000,
  "fixed_audio_window_sec": 15.0,
  "fixed_mel_frames": 1501,
  "fixed_encoder_frames": 188
}
Conversion Details
  • Conversion Tool : coremltools 9.0b1
  • Source Framework : PyTorch 2.7.0 / NeMo 2.x
  • Conversion Date : 2025-12-01
  • Conversion Method : Fixed-shape tracing (mobius approach)
License

This model conversion follows the license of the original model: CC-BY-4.0

Citation

If you use this model, please cite the original NVIDIA Parakeet model:

@misc{nvidia_parakeet_tdt_ja,
  title={Parakeet TDT CTC 0.6B Japanese},
  author={NVIDIA},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/nvidia/parakeet-tdt_ctc-0.6b-ja}
}
Acknowledgments

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53
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3-day runs
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7-day runs
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