README.md

metadata

language:
  - en
  - zh
license: apache-2.0
task_categories:
  - automatic-speech-recognition
pretty_name: Voices in the Wild
tags:
  - audio
  - speech
  - asr
  - robustness
  - noisy-speech
configs:
  - config_name: default
    data_files:
      - split: distortion
        path: data/distortion-*.parquet
      - split: distortion_dropout
        path: data/distortion_dropout-*.parquet
      - split: distortion_dropout_noise
        path: data/distortion_dropout_noise-*.parquet
      - split: distortion_noise
        path: data/distortion_noise-*.parquet
      - split: dropout
        path: data/dropout-*.parquet
      - split: echo
        path: data/echo-*.parquet
      - split: echo_distortion
        path: data/echo_distortion-*.parquet
      - split: echo_distortion_dropout
        path: data/echo_distortion_dropout-*.parquet
      - split: echo_distortion_dropout_noise
        path: data/echo_distortion_dropout_noise-*.parquet
      - split: echo_dropout
        path: data/echo_dropout-*.parquet
      - split: echo_noise
        path: data/echo_noise-*.parquet
      - split: echo_recording
        path: data/echo_recording-*.parquet
      - split: echo_recording_distortion
        path: data/echo_recording_distortion-*.parquet
      - split: echo_recording_distortion_dropout
        path: data/echo_recording_distortion_dropout-*.parquet
      - split: echo_recording_distortion_dropout_noise
        path: data/echo_recording_distortion_dropout_noise-*.parquet
      - split: echo_recording_distortion_noise
        path: data/echo_recording_distortion_noise-*.parquet
      - split: echo_recording_dropout
        path: data/echo_recording_dropout-*.parquet
      - split: echo_recording_dropout_noise
        path: data/echo_recording_dropout_noise-*.parquet
      - split: far_field
        path: data/far_field-*.parquet
      - split: far_field_distortion
        path: data/far_field_distortion-*.parquet
      - split: far_field_distortion_dropout
        path: data/far_field_distortion_dropout-*.parquet
      - split: far_field_distortion_dropout_noise
        path: data/far_field_distortion_dropout_noise-*.parquet
      - split: far_field_dropout
        path: data/far_field_dropout-*.parquet
      - split: far_field_noise
        path: data/far_field_noise-*.parquet
      - split: far_field_recording
        path: data/far_field_recording-*.parquet
      - split: far_field_recording_distortion
        path: data/far_field_recording_distortion-*.parquet
      - split: far_field_recording_distortion_dropout
        path: data/far_field_recording_distortion_dropout-*.parquet
      - split: far_field_recording_distortion_dropout_noise
        path: data/far_field_recording_distortion_dropout_noise-*.parquet
      - split: far_field_recording_distortion_noise
        path: data/far_field_recording_distortion_noise-*.parquet
      - split: far_field_recording_dropout
        path: data/far_field_recording_dropout-*.parquet
      - split: far_field_recording_dropout_noise
        path: data/far_field_recording_dropout_noise-*.parquet
      - split: noise
        path: data/noise-*.parquet
      - split: noise_dropout
        path: data/noise_dropout-*.parquet
      - split: obstructed
        path: data/obstructed-*.parquet
      - split: obstructed_distortion
        path: data/obstructed_distortion-*.parquet
      - split: obstructed_distortion_dropout
        path: data/obstructed_distortion_dropout-*.parquet
      - split: obstructed_distortion_dropout_noise
        path: data/obstructed_distortion_dropout_noise-*.parquet
      - split: obstructed_dropout
        path: data/obstructed_dropout-*.parquet
      - split: obstructed_noise
        path: data/obstructed_noise-*.parquet
      - split: obstructed_recording
        path: data/obstructed_recording-*.parquet
      - split: obstructed_recording_distortion
        path: data/obstructed_recording_distortion-*.parquet
      - split: obstructed_recording_distortion_dropout
        path: data/obstructed_recording_distortion_dropout-*.parquet
      - split: obstructed_recording_distortion_dropout_noise
        path: data/obstructed_recording_distortion_dropout_noise-*.parquet
      - split: obstructed_recording_distortion_noise
        path: data/obstructed_recording_distortion_noise-*.parquet
      - split: obstructed_recording_dropout
        path: data/obstructed_recording_dropout-*.parquet
      - split: obstructed_recording_dropout_noise
        path: data/obstructed_recording_dropout_noise-*.parquet
      - split: recording
        path: data/recording-*.parquet
      - split: recording_distortion
        path: data/recording_distortion-*.parquet
      - split: recording_distortion_dropout
        path: data/recording_distortion_dropout-*.parquet
      - split: recording_distortion_dropout_noise
        path: data/recording_distortion_dropout_noise-*.parquet
      - split: recording_distortion_noise
        path: data/recording_distortion_noise-*.parquet
      - split: recording_dropout
        path: data/recording_dropout-*.parquet
      - split: recording_dropout_noise
        path: data/recording_dropout_noise-*.parquet
      - split: recording_noise
        path: data/recording_noise-*.parquet
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: file_name
      dtype: string
    - name: audio_path
      dtype: string
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: text
      dtype: string
    - name: subset
      dtype: string
    - name: prediction
      dtype: string
    - name: name
      dtype: string
    - name: index
      dtype: int64

Voices in the Wild

Project Page | Paper | GitHub

Voices in the Wild (Voices-in-the-Wild-2M) is a large-scale automatic speech recognition (ASR) dataset designed for robustness training and evaluation under diverse, real-world acoustic conditions. It covers 7 classic acoustic phenomena (including noise, far-field speech, obstruction, echo/reverberation, recording artifacts, electronic distortion, and transmission dropout) and 54 physically plausible compound scenarios.

The dataset was introduced as part of the Mega-ASR framework to address the "acoustic robustness bottleneck" where models produce omissions or hallucinations under severe compositional distortions.

Data Fields

• file_name: relative path to the audio file.
• audio_path: audio path retained for local tooling.
• 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: 645,925
• Subset categories: 54

Loading

from datasets import load_dataset, Audio

# Load the dataset from the Hub
ds = load_dataset("zhifeixie/Voices-in-the-Wild-2M")
ds = ds.cast_column("audio", Audio())

# Access an example
print(ds["far_field"][0])

Citation

@misc{xie2026megaasrinthewild2speechrecognition,
      title={Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation},
      author={Zhifei Xie and Kaiyu Pang and Haobin Zhang and Deheng Ye and Xiaobin Hu and Shuicheng Yan and Chunyan Miao},
      year={2026},
      eprint={2605.19833},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2605.19833},
}