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Arabic Speaker Embeddings extracted from ASC and ClArTTS
There is one speaker embedding for each utterance in the validation set of both datasets. The speaker embeddings are 512-element X-vectors.
Arabic Speech Corpus has 100 files for a single male speaker and ClArTTS has 205 files for a single male speaker.
The X-vectors were extracted using this script, which uses the speechbrain/spkrec-xvect-voxceleb model.
Usage:
from datasets import load_dataset
embeddings_dataset = load_dataset("herwoww/arabic_xvector_embeddings", split="validation")
speaker_embedding = torch.tensor(embeddings_dataset[1]["speaker_embeddings"]).unsqueeze(0)
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