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Found 2 papers, 1 papers with code
DECAR: Deep Clustering for learning general-purpose Audio Representations
We introduce DECAR, a self-supervised pre-training approach for learning general-purpose audio representations.
S-vectors and TESA: Speaker Embeddings and a Speaker Authenticator Based on Transformer Encoder
Our experiments show that the performance of s-vectors with TESA is better than s-vectors with conventional PLDA-based speaker verification.
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