shangeth/vctk-mimi-codes

VCTK — Mimi Codes (mic1)

Pre-extracted Kyutai Mimi tokens for the VCTK Corpus — 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
• Codec: kyutai/mimi @ 24 kHz, 12.5 fps
• Resampling: 48 kHz → 24 kHz
• Filter: file column stem must end with _mic1

Usage

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"])

Links

• Dataset extraction code: github.com/shangeth/wren-datasets
• Wren research project: github.com/shangeth/wren
• TTS models trained on these codes: github.com/shangeth/wren-tts

Citation

@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.