Datasets:
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---
license: cc-by-4.0
size_categories:
- 100K<n<1M
task_categories:
- audio-classification
pretty_name: VocalSimilarity
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: label
dtype: string
- name: speaker
dtype: string
- name: subset
dtype: string
splits:
- name: train
num_bytes: 21758664803.439
num_examples: 269523
download_size: 0
dataset_size: 21758664803.439
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
### Dataset Description
This multi-species dataset was customized to benchmark k-NN retrieval and cluster separation tecniques on Human and Songbird vocalizations.
## Download Dataset
```python
from huggingface_hub import snapshot_download
snapshot_download('anonymous-submission000/vocsim', local_dir = "data/vocsim", repo_type="dataset" )
```
For more usage details, please refer to the GitHub repository: https://anonymous.4open.science/anonymize/neural_embeddings-6EE5
### Data Fields
1. **Subset**: Specifies the subset/category of the dataset. It can indicate whether the sample is from humans or songbirds, and possibly more detailed categorization.
2. **Audio**: Contains the audio sample.
3. **Label**: Represents the label or class of the audio clip, indicating the type of vocalization or sound.
4. **Speaker**: Identifies the speaker or source of the vocalization in the case of human datasets, or the individual bird in the case of songbird datasets.
### Human Datasets
1. [**AMI**](https://groups.inf.ed.ac.uk/ami/corpus/): The AMI Meeting Corpus comprises 100 hours of multi-modal meeting recordings, including audio data for utterances, words, and vocal sounds, alongside detailed speaker metadata.
2. [**TIMIT**](https://catalog.ldc.upenn.edu/LDC93S1): The TIMIT dataset contains manual phonetic transcriptions of utterances read by 630 English speakers with various dialects.
3. [**VocImSet**](https://zenodo.org/records/1340763): The Vocal Imitation Set contains recordings of 236 unique sound sources being imitated by 248 speakers.
4. [**VocalSketch**](https://zenodo.org/records/1251982): The Vocal Sketch Dataset contains two sets of 10'705 and 5'700 imitations respectively of 240 sounds.
### Songbird Datasets
1. [**DAS**](https://elifesciences.org/articles/68837): The Deep Audio Segmenter Dataset features single male Bengalese finch songs, including 473 vocalizations of 6 vocalization types.
2. [**Tomka**](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/655689/2023.09.04.555475v1.full.pdf): The Gold-Standard Zebrafinch dataset contains 48,059 vocalizations of 36 vocalization types from 4 zebra finches.
3. [**Nicholson**](https://figshare.com/articles/dataset/Bengalese_Finch_song_repository/4805749/9): The Bengalese finch song repository includes songs of four Bengalese finches recorded in the Sober lab at Emory University and manually clustered by two authors.
4. [**Elie**](https://figshare.com/articles/dataset/Vocal_repertoires_from_adult_and_chick_male_and_female_zebra_finches_Taeniopygia_guttata_/11905533/1): Vocal repertoires from zebra finches, collected between 2011 and 2014 at the University of California Berkeley by Julie E Elie. This dataset contains 3,500 vocalizations from 50 individuals and 65 vocalization types.
## Contact |