feat(stt/parakeet): decode-loop fusion campaign — TDT v3 + EOU (LSTM gate + B1 fusion)#68
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feat(stt/parakeet): decode-loop fusion campaign — TDT v3 + EOU (LSTM gate + B1 fusion)#68Alex-Wengg wants to merge 1 commit into
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LSTM gate: ios17.lstm in both prediction networks -> ANE categorically blocked (Kokoro PostAlbert finding); campaign is fusion-only. Fused decoder+joint_decision into one CoreML dispatch per step: - TDT v3: 1.27x/step vs shipped pair, 1.11x utterance decode loop (~2 ms/utt; fused pays LSTM on blank steps production skips) - EOU: 1.23x/step, 1.21x utterance decode loop (~7-10 ms/utt; 458 -> 229 dispatches) Parity: token/duration/state bit-identical vs two-model chain (fp32); top_k_logits 7e-4/1e-3 reassociation noise only. fp16 export only -- fp32 fused regresses 0.64x when GPU is in the compute-unit set. See models/stt/parakeet-tdt-v3-0.6b/coreml/OPTIMIZATION.md.
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Research record for the Parakeet decode-loop campaign:
ios17.lstmin both prediction networks (TDT v3 ×2, EOU ×1) → ANE placement categorically closed for all Parakeet RNN-T decodersmodels/stt/parakeet-tdt-v3-0.6b/coreml/OPTIMIZATION.md🤖 Generated with Claude Code