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Add CommonVoice ITTS controllability validation set (198 clips, age/gender/native_accent)
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---
license: cc0-1.0
task_categories:
- audio-classification
language:
- en
tags:
- speech
- controllability
- tts-evaluation
- age
- gender
- accent
pretty_name: CommonVoice ITTS Controllability Validation Set
configs:
- config_name: default
data_files:
- split: validation
path: metadata.jsonl
---
# CommonVoice ITTS Controllability Validation Set
Ground-truth-labelled English speech clips drawn from
[`fixie-ai/common_voice_17_0`](https://huggingface.co/datasets/fixie-ai/common_voice_17_0)
(Common Voice 17.0, CC0), used to validate audio-LM **judges** for
instructable-TTS (ITTS) controllability scoring on **age**, **gender**, and
**native accent**.
Each clip carries a human-provided attribute label from Common Voice, so a judge's
perceived-attribute accuracy can be measured against real ground truth (blind
perceived-accuracy protocol).
## Contents
- `data/*.mp3` — 198 source clips (~108 MB).
- `metadata.jsonl` — 271 rows, one per (clip, attribute).
Cells (30 per value unless noted):
| attribute | values |
|----------------|-----------------------------------------------------|
| age | young_adult, middle_aged, elderly |
| gender | female, male, non_binary (1) |
| native_accent | american, australian, british, indian |
Age bands: young_adult 13–39 / middle_aged 40–59 / elderly 60+.
## Fields
- `file_name` — relative path to the audio (AudioFolder convention).
- `id``<clip>-<attribute>`.
- `attribute` — one of `age` / `gender` / `native_accent`.
- `requested_label` — ground-truth Common Voice label for that attribute.
- `text` — reference transcript.
- `language``en`.
- `source``common_voice_17_0`.
A clip may appear under more than one attribute (same speaker labelled for age,
gender, and accent).
## Usage
```python
from datasets import load_dataset
ds = load_dataset("audiofolder", data_dir="<local_dir>", split="train")
```
## License
Audio is Common Voice 17.0 (CC0-1.0); labels derive from Common Voice contributor
metadata. See the upstream dataset for details.