Datasets:

SujithPulikodan
/

Vaani-sample-data

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 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

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:

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.