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README.md

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+---
+title: WeeMed AI
+emoji: 🩺
+colorFrom: blue
+colorTo: green
+---
+
+# WeeMed AI
+
+**Building a globally standardized, AI-driven digital health and long-term care platform
+for aging societies.**
+
+FHIR-first. Integrated health data, intelligent decision support, personalized preventive
+medicine — deployed in real clinics, health-screening centers, and community long-term
+care sites in Taiwan.
+
+> **AI accelerates digitization; it isn't the product.**
+
+A spin-off of the **Medical Image Processing Laboratory (MIPL)**, National Yunlin
+University of Science and Technology — a lab that has built AI-assisted diagnostic
+systems with National Taiwan University Hospital Yunlin Branch, National Cheng Kung
+University Hospital, and Dalin Tzu Chi Hospital since 2003.
+
+---
+
+## What we release here
+
+We ship models that fall out of real deployment problems, and we publish the
+**measurements**, not just the weights.
+
+### 🎙️ [Breeze-ASR-26-edge](https://huggingface.co/weemed/Breeze-ASR-26-edge)
+
+Taiwanese Hokkien (台語) + Mandarin speech recognition, quantized for the edge, in two
+runtimes — with a measured benchmark telling you which to pick:
+
+| Runtime | RTF (CPU, 4 threads) | Real-time? |
+|---|---|---|
+| CTranslate2 / faster-whisper | **0.18 – 0.23** | ✅ |
+| ONNX / sherpa-onnx | 1.17 – 1.76 | ❌ (but runs on Android/iOS/WASM) |
+
+Measured on real multi-speaker meeting audio, not synthetic clips. Derived from
+[MediaTek-Research/Breeze-ASR-26](https://huggingface.co/MediaTek-Research/Breeze-ASR-26)
+(Apache-2.0) — all credit for the model to MediaTek Research.
+
+---
+
+## Why this matters to us
+
+Taiwan is aging fast, and the people doing the caring — nurses at screening centers,
+care managers at community sites, elders themselves — mostly do not speak to each other
+in written Mandarin. They speak **Taigi**, in noisy rooms, on tablets held in one hand.
+
+Health tech that only understands clean written Mandarin does not meet them where they
+are. So we work on the unglamorous end of clinical AI: the languages actually spoken,
+the devices actually held, the constraints actually present.
+
+---
+
+## How we publish
+
+- **Honest benchmarks.** We report the number that survives scrutiny, including when it
+  kills our own hypothesis. Our ASR card documents the measurement traps we fell into
+  before publishing (short clips and repetitive audio both give flattering, wrong RTFs).
+- **Named gaps.** What we could not measure is written down as an open gap, not omitted.
+- **Real audio, real clinics.** Benchmarks on synthetic data tell you about synthetic data.
+
+---
+
+<sub>Apache-2.0 unless stated otherwise · Made in Yunlin, Taiwan</sub>