Datasetpublic

heogit2/cmu-arctic-xvectors

Speaker embeddings extracted from CMU ARCTIC There is one .npy file for each utterance in the dataset, 7931 files in total. The speaker embeddings are 512-element X-vectors. The CMU ARCTIC dataset divides the utterances among the following speakers: bdl (US male) slt (US female) jmk (Canadian male) awb (Scottish male) rms (US male) clb (US female) ksp (Indian male) The X-vectors were extracted using this script, which uses the speechbrain/spkrec-xvect-voxceleb model. Usage:… See the full description on the dataset page: https://huggingface.co/datasets/heogit2/cmu-arctic-xvectors.

sourceHugging Facemitupdated 4mo agoView on Hugging Face

0likes8downloads

Dataset Card

Speaker embeddings extracted from CMU ARCTIC

There is one .npy file for each utterance in the dataset, 7931 files in total. The speaker embeddings are 512-element X-vectors.

The CMU ARCTIC dataset divides the utterances among the following speakers:

—bdl (US male)
—slt (US female)
—jmk (Canadian male)
—awb (Scottish male)
—rms (US male)
—clb (US female)
—ksp (Indian male)

The X-vectors were extracted using this script, which uses the speechbrain/spkrec-xvect-voxceleb model.

Usage:

python

from datasets import load_dataset
embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")

speaker_embeddings = embeddings_dataset[7306]["xvector"]
speaker_embeddings = torch.tensor(speaker_embeddings).unsqueeze(0)