Datasets:
| license: openrail | |
| dataset_info: | |
| features: | |
| - name: audio | |
| dtype: | |
| audio: | |
| sampling_rate: 16000 | |
| - name: label | |
| dtype: int64 | |
| - name: is_unknown | |
| dtype: bool | |
| - name: speaker_id | |
| dtype: string | |
| - name: utterance_id | |
| dtype: int8 | |
| - name: logits | |
| sequence: float32 | |
| - name: Probability | |
| dtype: float64 | |
| - name: Predicted Label | |
| dtype: string | |
| - name: Annotated Labels | |
| dtype: string | |
| - name: embedding | |
| sequence: float32 | |
| - name: embedding_reduced | |
| sequence: float32 | |
| splits: | |
| - name: train | |
| num_bytes: 2137341907.375 | |
| num_examples: 60973 | |
| download_size: 2094280286 | |
| dataset_size: 2137341907.375 | |
| This dataset is an extended version of the MIT/ast-finetuned-speech-commands-v2 dataset. | |
| It provides predicted labels, their annotations and embeddings, trained with Huggingface's AutoModel and | |
| AutoFeatureExtractor. If you would like to have a closer look at the dataset and model's performance, you can use Spotlight by Renumics to find complex sub-relationships between classes. |