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.
import CoreML
// Load modelslet encoder =tryMLModel(contentsOf: encoderURL)
let decoder =tryMLModel(contentsOf: decoderURL)
let joint =tryMLModel(contentsOf: jointURL)
// Or use the fused mel_encoder for simpler pipelinelet melEncoder =tryMLModel(contentsOf: melEncoderURL)
Important Notes
Fixed Input Shapes
: Models use fixed shapes for stability. Audio must be padded/trimmed to 15 seconds (240,000 samples at 16kHz).
Encoder Output Format
: Japanese model outputs
(B, features, time)
=
(1, 1024, T)
, different from English v3 models which output
(B, T, features)
.
Greedy Decoding
: Use standard TDT greedy decoding with the decoder and joint networks.
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