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20152026
most citedCN-CELEB: a challenging Chinese speaker recognition dataset

13 citations · 126 across the 71 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.CL2023

A Glance is Enough: Extract Target Sentence By Looking at A keyword

Ying Shi, Dong Wang, Lantian Li +1

This paper investigates the possibility of extracting a target sentence from multi-talker speech using only a keyword as input. For example, in social security applications, the ke…

cs.SD2023

An Investigation of Distribution Alignment in Multi-Genre Speaker Recognition

Zhenyu Zhou, Junhui Chen, Namin Wang +2

Multi-genre speaker recognition is becoming increasingly popular due to its ability to better represent the complexities of real-world applications. However, a major challenge is t…

cs.SD2023★ 1 cited

Multi-Domain Adaptation by Self-Supervised Learning for Speaker Verification

Wan Lin, Lantian Li, Dong Wang

In real-world applications, speaker recognition models often face various domain-mismatch challenges, leading to a significant drop in performance. Although numerous domain adaptat…

cs.SD2023

Spot keywords from very noisy and mixed speech

Ying Shi, Dong Wang, Lantian Li +2

Most existing keyword spotting research focuses on conditions with slight or moderate noise. In this paper, we try to tackle a more challenging task: detecting keywords buried unde…

cs.SD2023★ 1 cited

A Multi-Scale Attentive Transformer for Multi-Instrument Symbolic Music Generation

Xipin Wei, Junhui Chen, Zirui Zheng +3

Recently, multi-instrument music generation has become a hot topic. Different from single-instrument generation, multi-instrument generation needs to consider inter-track harmony b…

cs.SD2023

Visualizing data augmentation in deep speaker recognition

Pengqi Li, Lantian Li, Askar Hamdulla +1

Visualization is of great value in understanding the internal mechanisms of neural networks. Previous work found that LayerCAM is a reliable visualization tool for deep speaker mod…

cs.SD2023

Ordered and Binary Speaker Embedding

Jiaying Wang, Xianglong Wang, Namin Wang +2

Modern speaker recognition systems represent utterances by embedding vectors. Conventional embedding vectors are dense and non-structural. In this paper, we propose an ordered bina…

cs.CV2023

CN-Celeb-AV: A Multi-Genre Audio-Visual Dataset for Person Recognition

Lantian Li, Xiaolou Li, Haoyu Jiang +3

Audio-visual person recognition (AVPR) has received extensive attention. However, most datasets used for AVPR research so far are collected in constrained environments, and thus ca…