| --- |
| language: |
| - en |
| license: mit |
| size_categories: |
| - 10K<n<100K |
| task_categories: |
| - audio-classification |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| dataset_info: |
| features: |
| - name: speaker_id |
| dtype: string |
| - name: audio |
| dtype: |
| audio: |
| sampling_rate: 16000 |
| - name: digit |
| dtype: |
| class_label: |
| names: |
| '0': '0' |
| '1': '1' |
| '2': '2' |
| '3': '3' |
| '4': '4' |
| '5': '5' |
| '6': '6' |
| '7': '7' |
| '8': '8' |
| '9': '9' |
| - name: gender |
| dtype: |
| class_label: |
| names: |
| '0': male |
| '1': female |
| - name: accent |
| dtype: string |
| - name: age |
| dtype: int64 |
| - name: native_speaker |
| dtype: bool |
| - name: origin |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1493209727.0 |
| num_examples: 24000 |
| - name: test |
| num_bytes: 360966680.0 |
| num_examples: 6000 |
| download_size: 1483680961 |
| dataset_size: 1854176407.0 |
| --- |
| # Dataset Card for "AudioMNIST" |
| The [audioMNIST](https://github.com/soerenab/AudioMNIST) dataset has 50 English recordings per digit (0-9) of 60 speakers. |
| There are 60 participants in total, with 12 being women and 48 being men, all featuring a diverse range of accents and country of origin. Their ages vary from 22 to 61 years old. This is a great dataset to explore a simple audio classification problem: either the digit or the gender. |
|
|
| ## Bias, Risks, and Limitations |
| * The genders represented in the dataset are unbalanced, with around 80% being men. |
| * The majority of the speakers, around 70%, have a German accent |
|
|
| ### Citation Information |
| The original creators of the dataset ask you to cite [their paper](https://arxiv.org/abs/1807.03418) if you use this data: |
|
|
| ``` |
| @ARTICLE{becker2018interpreting, |
| author = {Becker, S\"oren and Ackermann, Marcel and Lapuschkin, Sebastian and M\"uller, Klaus-Robert and Samek, Wojciech}, |
| title = {Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals}, |
| journal = {CoRR}, |
| volume = {abs/1807.03418}, |
| year = {2018}, |
| archivePrefix = {arXiv}, |
| eprint = {1807.03418}, |
| } |
| ``` |
