Datasets:
File size: 1,763 Bytes
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---
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: string
splits:
- name: train
num_bytes: 1492088102.0
num_examples: 24000
- name: test
num_bytes: 360692430.0
num_examples: 6000
download_size: 1483317200
dataset_size: 1852780532.0
---
# Dataset Card for "AudioMNIST"
This is just a reupload of the [audioMNIST](https://github.com/soerenab/AudioMNIST) dataset for convenient use with the datasets library. For each speaker (12 female, 48 male), there are 50 recordings of each digit.
I created an 80/20 train test split, making sure that no speaker is contained in both the train and the test.
### 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},
}
``` |