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Mattt releases Swift packages for on-device speech and decisions

AI summary

Mattt announced AnySpeechRecognizer and AnyDecisionModel, two Swift packages for Apple platforms. AnySpeechRecognizer mirrors Apple’s speech-to-text API, supports selectable engines such as NVIDIA Parakeet and Alibaba Qwen3-ASR running locally through Core ML, and adds speaker diarization. AnyDecisionModel returns typed answers and probabilities for yes-or-no, multiple-choice, and rating-scale questions, using on-device models through MLX, Core AI, or llama.cpp, or decision models from Jev or Ollama. The packages can download open models from Hugging Face. Reported speed, memory, and word-error-rate results came from one machine and a few datasets; testing was limited to macOS 27, with no iPhone results.

In-depth insight

The packages provide familiar Swift interfaces for local speech recognition and model-based decisions. AnyDecisionModel exposes each answer’s probability rather than requiring developers to generate and parse text.

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Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms

Published October 29, 2026

Update on GitHub

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Mattt mattt

#AnySpeechRecognizer#AnyDecisionModel#Apple#NVIDIA Parakeet#Alibaba Qwen3-ASR#MLX#Core AI#llama.cpp#Jev#Ollama#Moondream Parakeet Ultra

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