File size: 3,639 Bytes
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dataset_info:
- config_name: audio
features:
- name: audio
dtype: audio
- name: file_name
dtype: string
- name: transcript
dtype: string
- name: speakerID
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: state
dtype: string
- name: district
dtype: string
- name: pincode
dtype: string
- name: duration
dtype: float32
- name: languagesKnown
dtype: string
- name: stay_years
dtype: string
- name: isTranscriptionAvailable
dtype: string
- name: referenceImage
dtype: string
- name: speakerImageHash
dtype: string
- name: UtteranceSequenceID
dtype: int32
splits:
- name: train
num_bytes: 218646505
num_examples: 1302
download_size: 214669976
dataset_size: 218646505
- config_name: images
features:
- name: image
dtype: image
- name: file_name
dtype: string
splits:
- name: train
num_bytes: 160409135
num_examples: 973
download_size: 160426214
dataset_size: 160409135
configs:
- config_name: audio
data_files:
- split: train
path: audio/train-*
- config_name: images
data_files:
- split: train
path: images/train-*
---
# Vaani Sample Data — Andhra Pradesh / Annamaya
A small sample slice of the [ARTPARK-IISc/VAANI](https://huggingface.co/datasets/ARTPARK-IISc/VAANI) dataset, covering the `AndhraPradesh_Annamaya` subset.
## Configs
| Config | Split | Rows | Description |
|----------|-------|-----:|-------------|
| `audio` | train | 1,302 | Telugu speech utterances with transcripts and speaker metadata. |
| `images` | train | 973 | Reference images cited via `referenceImage` in the audio config (973 unique images across the 1,302 audio rows). |
## Loading
```python
from datasets import load_dataset
audio = load_dataset("SujithPulikodan/Vaani-sample-data", "audio", split="train")
images = load_dataset("SujithPulikodan/Vaani-sample-data", "images", split="train")
```
## Schema
### `audio`
| Column | Type | Notes |
|---|---|---|
| `audio` | `Audio` | Embedded audio (WAV bytes + path). |
| `file_name` | `string` | Audio basename. |
| `transcript` | `string` | Telugu transcription. May contain `<noise>` markers. |
| `speakerID` | `string` | Stable speaker identifier. |
| `language` | `string` | Spoken language (Telugu). |
| `gender` | `string` | Speaker gender. |
| `state`, `district`, `pincode` | `string` | Recording location. |
| `duration` | `float32` | Seconds. |
| `languagesKnown` | `string` | Stringified list, e.g. `['Telugu']`. |
| `stay_years` | `string` | How long the speaker has lived in the district. |
| `isTranscriptionAvailable` | `string` | `Yes`/`No` (always `Yes` after filtering). |
| `referenceImage` | `string` | Path of the prompt image shown to the speaker (matches a row in the `images` config). |
| `speakerImageHash` | `string` | Hash of the speaker's image. |
| `UtteranceSequenceID` | `int32` | Sequence index within a session. |
### `images`
| Column | Type | Notes |
|---|---|---|
| `image` | `Image` | JPEG bytes. |
| `file_name` | `string` | Image basename, matches the basename in `audio.referenceImage`. |
To join an audio row with its image:
```python
import os
imgs_by_name = {row["file_name"]: row["image"] for row in images}
def image_for(audio_row):
return imgs_by_name[os.path.basename(audio_row["referenceImage"])]
```
## Source & License
Derived from **ARTPARK-IISc/VAANI** by IISc / ARTPARK. Refer to the upstream dataset card for the original license and terms of use; this redistribution inherits them. Please cite the upstream project when using this data.
|