datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
echo-embeddings-expresso-tar
Expresso Speaker Embeddings (tarred)
Items: 17
This dataset ships as a single tar at the repo root. Members preserve paths like
Expresso/<id>/audio.mp3 and Expresso/<id>/speaker_latent.safetensors.
See loader.py for example loading.
Attribution:
Contains audio and embeddings derived from the Expresso dataset (INTERSPEECH 2023). Distributed under CC BY-NC 4.0; attribution required; commercial use is not permitted.
echo-embeddings-vctk-tar
VCTK Speaker Embeddings (tarred)
Items: 109
This dataset ships as a single tar at the repo root. Members preserve paths like
VCTK/<id>/audio.mp3 and VCTK/<id>/speaker_latent.safetensors.
See loader.py for example loading.
Attribution:
Contains audio and embeddings derived from the CSTR VCTK Corpus. Distributed under CC BY 4.0; attribution required.
uk-pods
uk-pods - speech datasets of Ukrainian podcasts.
Preparation
Clone the dataset repository and extract the content of clips.tar.gz archive.
git clone https://huggingface.co/datasets/taras-sereda/uk-pods
cd uk-pods && tar -zxvf clips.tar.gz
To use these manifests for training/inference with NeMo [1] modify audio_filepath to absolute locations of audio files extracted in previous step.
# data_root=<clonned_repo_dir> # /home/ubuntu/uk-pods
data_root=$(realpath .)
sed -i… See the full description on the dataset page: https://huggingface.co/datasets/taras-sereda/uk-pods.echo-embeddings-ears-tar
EARS Speaker Embeddings (tarred)
Items: 2568
This dataset ships as a single tar at the repo root. Members preserve paths like
EARS/<id>/audio.mp3 and EARS/<id>/speaker_latent.safetensors.
See loader.py for example loading.
Attribution:
Contains audio and embeddings derived from the EARS dataset. Distributed under CC BY-NC 4.0; attribution required; commercial use is not permitted.