Add/expand dataset card

README.md

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   - split: train
     path: data/train-*
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+
+# TR↔HI Parallel Text
+
+**65,662** aligned text triples — English pivot plus Turkish and Hindi
+(`en_text` / `tr_text` / `hi_text`), each tagged with its `source`.
+
+This is the **text layer** the speech corpora were synthesised from: these
+sentences were sent to TTS to produce
+[`tr-hi-parallel-speech-v2`](https://huggingface.co/datasets/tiny-aya-translate/tr-hi-parallel-speech-v2),
+which was then Mimi-encoded into
+[`tr-hi-mimi-encoded`](https://huggingface.co/datasets/tiny-aya-translate/tr-hi-mimi-encoded).
+
+Text-only, ~10 MB, no audio. Sources include FLORES, OPUS-100, and
+machine-translated conversational data — check `source` per row, since the
+licence terms differ by origin (FLORES is share-alike).
+
+## Project
+
+Part of **TinyAya Stage 2** — Turkish⇄Hindi speech-to-speech translation with a
+text inner-monologue (Cohere2 + LoRA, frozen Moshi depth decoder, Mimi codes).
+
+- **Model:** [`tiny-aya-translate/tr-hi-s2st-v0.3`](https://huggingface.co/tiny-aya-translate/tr-hi-s2st-v0.3)
+- **Code:** [tiny-aya-simultaneous-translation/model](https://github.com/tiny-aya-simultaneous-translation/model)
+- **Results:** [v0.3 evaluation report](https://github.com/tiny-aya-simultaneous-translation/model/blob/main/docs/v0.3-eval-report.md)
+- **Blog:** [Adapting Moshi for Low-Resource Speech Translation](https://labscommunity.cohere.com/blog/2026/adapting-moshi-low-resource-speech-translation/)
+
+## Licence
+
+Text originates from **FLORES** (CC BY-SA 4.0 — **share-alike propagates to
+derivatives**), **OPUS-100** (per-subcorpus terms) and machine-translated
+conversational sources; speech is **synthetic TTS output** and inherits each TTS
+model's terms. Review the upstream terms before redistribution; see
+[`THIRD_PARTY_NOTICES.md`](https://github.com/tiny-aya-simultaneous-translation/model/blob/main/THIRD_PARTY_NOTICES.md).