| | --- |
| | dataset_info: |
| | features: |
| | - name: audio |
| | dtype: audio |
| | - name: label |
| | dtype: |
| | class_label: |
| | names: |
| | '0': down |
| | '1': 'on' |
| | splits: |
| | - name: train |
| | num_bytes: 117237120.74 |
| | num_examples: 3706 |
| | - name: validation |
| | num_bytes: 16469406.0 |
| | num_examples: 521 |
| | - name: test |
| | num_bytes: 15996007.0 |
| | num_examples: 499 |
| | download_size: 135214158 |
| | dataset_size: 149702533.74 |
| | --- |
| | # Dataset Card for "down_on" |
| | |
| | This is a demo dataset for acoustic classification, consisting of utterances of *down* and *on* extracted from the |
| | `superb ks` dataset. |
| | |
| | `down_on_hub.py` illustrates the methodology for creating such a dataset from wav files. |
| | `down_on_copy.py` was used to write the wav files. |
| | `down_on_create.py` is the more direct method. |
| | |
| | See the model `MatsRooth/wav2vec2-base_down_on` for the demo application. |
| | |
| | |
