Update dataset card

README.md

@@ -1,30 +1,79 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: text
-    dtype: string
-  - name: speaker_id
-    dtype: int32
-  - name: accent
-    dtype: string
-  - name: codes
-    list:
-      list: int16
-  - name: n_frames
-    dtype: int32
-  - name: k_codebooks
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 35510068
-    num_examples: 44283
-  download_size: 21693746
-  dataset_size: 35510068
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- text-to-speech
+tags:
+- mimi
+- neural-codec
+- speech-synthesis
+- vctk
+- audio-tokens
+- accents
+pretty_name: VCTK Mimi Codes (mic1)
+size_categories:
+- 10K<n<100K
 ---
+
+# VCTK — Mimi Codes (mic1)
+
+Pre-extracted [Kyutai Mimi](https://huggingface.co/kyutai/mimi) tokens for the
+[VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/2950) — 109 speakers across
+11 British, Scottish, and American accents. ~44h of read speech.
+
+**Only mic1 recordings are included.** Each utterance was recorded with two
+microphones; mic1 (close microphone) gives a cleaner signal. Mic2 duplicates are
+excluded. Utterance IDs end in `_mic1` (e.g. `p225_001_mic1`).
+
+## Schema
+
+| Column | Type | Notes |
+|---|---|---|
+| `id` | string | e.g. `p225_001_mic1` |
+| `text` | string | read sentence, mixed-case with punctuation |
+| `speaker_id` | int32 | numeric speaker ID (225 for p225) |
+| `accent` | string | e.g. `English`, `Scottish`, `American` |
+| `codes` | `int16[k=8][n_frames]` | Mimi codebook indices @ 12.5 fps |
+| `n_frames` | int32 | |
+| `k_codebooks` | int32 | 8 |
+
+## Extraction details
+
+- **Source:** [`sanchit-gandhi/vctk`](https://huggingface.co/datasets/sanchit-gandhi/vctk)
+- **Codec:** [`kyutai/mimi`](https://huggingface.co/kyutai/mimi) @ 24 kHz, 12.5 fps
+- **Resampling:** 48 kHz → 24 kHz
+- **Filter:** `file` column stem must end with `_mic1`
+
+## Usage
+
+```python
+from datasets import load_dataset
+import torch
+
+ds = load_dataset("shangeth/vctk-mimi-codes", split="train")
+ex = ds[0]
+codes = torch.tensor(ex["codes"], dtype=torch.long)  # [8, n_frames]
+print(ex["id"], ex["accent"], "→", ex["text"])
+```
+
+## Citation
+
+```bibtex
+@misc{wren2026,
+  title  = {Wren: A Family of Small Open-Weight Models for Unified Speech-Text Modelling},
+  author = {Shangeth Rajaa},
+  year   = {2026},
+  url    = {https://github.com/shangeth/wren}
+}
+
+@inproceedings{veaux2017cstr,
+  title     = {CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},
+  author    = {Veaux, Christophe and Yamagishi, Junichi and MacDonald, Kirsten},
+  year      = {2017}
+}
+```
+
+## License
+
+CC-BY-4.0.