Jun 28, 2022 · We propose a few-shot domain generalization framework that learns to tackle distribution shift for new users and new domains.
Jul 12, 2021 · This paper addresses this problem for speaker verification, which is the task of accept- ing or rejecting the claimed identity of a speaker test ...
Domain Agnostic Few-shot Learning for Speaker Verification
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Oct 26, 2022 · PDF | On Sep 18, 2022, Seunghan Yang and others published Domain Agnostic Few-shot Learning for Speaker Verification | Find, read and cite ...
Domain Agnostic Few-shot Learning for Speaker Verification. S. Yang, D. Das, J. Cho, H. Park, and S. Yun. INTERSPEECH, page 595-599. ISCA, (2022 ). 1.
Domain Agnostic Few-shot Learning for Speaker Verification. Seunghan Yang Debasmit Das Janghoon Cho Hyoungwoo Park Sungrack Yun. Published in: CoRR (2022).
This paper considers a semi-supervised learning framework for weakly labeled polyphonic sound event detection problems for the DCASE 2019 challenge's task4 by ...
Apr 17, 2019 · This paper proposes to identify speakers by learning from only a few training examples, using a deep neural network with prototypical loss ...
People also ask
What is the difference between speaker identification and speaker verification?
A similar idea of embedding adaptation has been proposed in few-shot learning (FSL) tasks in the computer vision domain [15]. To address the second ...
Existing methods for few-shot speaker identification (FSSI) obtain high accuracy, but their computational complexities and model sizes need to be reduced ...
In this paper, we introduce a new practical task, termed as cross-domain few-shot action recognition, and hypothesize there is a domain shift.