Parakeet TDT CTC 110M CoreML NVIDIA's Parakeet TDT CTC 110M model converted to CoreML format for efficient inference on Apple Silicon. Model Description This is a hybrid ASR model with a shared Conformer encoder and two decoder heads: CTC Head : Fast greedy decoding, ideal for keyword spotting TDT Head : Token Duration Transducer for high quality transcription Architecture Component Description Size Preprocessor Mel spectrogram extraction ~1 MB Encoder Conformer encoder (shared) ~400 MB CTCHead CTC output projection ~4 MB Decoder TDT prediction network (LSTM) ~25 MB JointDecision TDT joint network ~6 MB Total size : ~436 MB Performance Benchmarked on Earnings22 dataset (772 audio files): Metric Value Keyword Recall 100% (1309/1309) WER 17.97% RTFx (M4 Pro) 358x real time Requirements macOS 13+ (Ventura or later) Apple Silicon (M1/M2/M3/M4) Python 3.10+ Installation Usage Python Inference Command Line Model Conversion To convert from the original NeMo model: This will: 1. Download the original model from NVIDIA ( nvidia/parakeet tdt ctc 110m ) 2. Convert each component to CoreML format 3. Extract vocabulary and create metadata File Structure Decoding Modes TDT Mode (Recommended for…
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