zhifeixie/Voices-in-the-Wild-test

Voices in the Wild

Voices in the Wild is an automatic speech recognition dataset for robustness evaluation and training under diverse acoustic conditions. Each example contains an augmented speech waveform, a transcription, and a normalized acoustic subset label.

Repository Structure

Voices-in-the-Wild/
├── README.md
├── metadata.jsonl
├── meta.jsonl
└── audio/
    ├── noise/
    ├── far_field/
    ├── far_field_noise/
    └── ...

For Hugging Face loading, metadata.jsonl contains a repository-relative file_name field. The audio files use sequential public names such as sample_000000.wav.

Data Fields

• file_name: relative path to the audio file.
• audio_path: audio path retained for compatibility with local ASR tooling.
• audio: decoded by Hugging Face when loading from AudioFolder or Parquet.
• text: transcription alias copied from answer.
• answer: reference transcription.
• question: transcription instruction.
• subset: normalized acoustic condition category.
• prediction: empty placeholder for model output.
• name: public sample identifier.
• index: integer sample index.

Dataset Size

• Total examples: 590499
• Subset categories: 37
• Audio format: WAV

Subset Distribution

subset	count
noise	89418
far_field_noise	76044
barrier	42826
echo	42620
far_field	42610
distortion	42575
dropout	42478
recording	42353
far_field_dropout	30300
noise_dropout	29886
far_field_recording	29854
barrier_dropout	3197
echo_dropout	3150
echo_noise	3130
far_field_recording_distortion	3113
echo_distortion_dropout_noise	3102
echo_recording_dropout	3100
echo_recording_distortion_noise	3098
barrier_distortion	3095
echo_distortion_dropout	3090
echo_recording_dropout_noise	3088
echo_recording_distortion_dropout	3079
echo_recording_distortion_dropout_noise	3073
recording_distortion_dropout_noise	3072
far_field_distortion_dropout_noise	3063
echo_distortion	3061
echo_recording_distortion	3056
echo_recording	3040
barrier_recording	3032
far_field_recording_dropout	3032
far_field_recording_distortion_dropout	3004
far_field_distortion	3003
barrier_noise	2995
far_field_recording_distortion_noise	2990
far_field_distortion_dropout	2963
far_field_recording_dropout_noise	2957
far_field_recording_distortion_dropout_noise	2952

Loading

from datasets import load_dataset, Audio

ds = load_dataset("Prummn/Voices-in-the-Wild")
ds = ds.cast_column("audio", Audio())
print(ds["train"][0])

For local AudioFolder loading:

from datasets import load_dataset, Audio

ds = load_dataset("audiofolder", data_dir="/data/haobin/Voices-in-the-Wild")
ds = ds.cast_column("audio", Audio())

Parquet Format

The recommended upload format stores audio bytes directly inside Parquet shards. The audio column is a Hugging Face-compatible struct with bytes and path fields. Metadata fields such as text, answer, subset, name, and index are stored in the same rows.