Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Speaker Recognition with Transformers Using wav2vec 2.0   Recent advances in unsupervised speech representation learning discover new
approaches and provide new state-of-the-art for diverse types of speech
processing tasks. This paper presents an investigation of using wav2vec 2.0
deep speech representations for the speaker recognition task. The proposed
fine-tuning procedure of wav2vec 2.0 with simple TDNN and statistic pooling
back-end using additive angular margin loss allows to obtain deep speaker
embedding extractor that is well-generalized across different domains. It is
concluded that Contrastive Predictive Coding pretraining scheme efficiently
utilizes the power of unlabeled data, and thus opens the door to powerful
transformer-based speaker recognition systems. The experimental results
obtained in this study demonstrate that fine-tuning can be done on relatively
small sets and a clean version of data. Using data augmentation during
fine-tuning provides additional performance gains in speaker verification. In
this study speaker recognition systems were analyzed on a wide range of
well-known verification protocols: VoxCeleb1 cleaned test set, NIST SRE 18
development set, NIST SRE 2016 and NIST SRE 2019 evaluation set, VOiCES
evaluation set, NIST 2021 SRE, and CTS challenges sets.

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The categories of this paper are: gr-qc
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-th
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The categories of this paper are: stat
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The categories of this paper are: nlin
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The categories of this paper are: solv-int
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The categories of this paper are: mtrl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: dg-ga
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The categories of this paper are: q-fin
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
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The categories of this paper are: supr-con