End-to-end speaker identification research based on multi-scale SincNet and CGAN-Reference-Cited by-同舟云学术

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End-to-end speaker identification research based on multi-scale SincNet and CGAN

Published:2023-08-02 Issue:30 Volume:35 Page:22209-22222
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Wei Guangcun^ORCID,Zhang Yanna,Min Hang,Xu Yunfei

Funder

State Grid Shandong electric power company science and technology support project, China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-08906-1.pdf

Reference48 articles.

1. Liu K, Zhou H (2020) Text-independent speaker verification with adversarial learning on short utterances. IEEE, pp 6569–6573

2. Chakroun R, Frikha M (2020) Robust features for text-independent speaker recognition with short utterances. Neural Comput Appl 32(17):13863–13883

3. Shon S, Ali A (2018) Glass J Convolutional neural networks and language embeddings for end-to-end dialect recognition. arXiv preprint arXiv:1803.04567

4. Jin Z et al (2021) Adversarial data augmentation for disordered speech recognition. arXiv preprint arXiv:2108.00899

5. Li C et al (2017) Deep speaker: an end-to-end neural speaker embedding system. arXiv preprint arXiv:1705.02304

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient Low-Complexity Speaker Identification based on a SpeakerGAN Approach;2024 34th International Conference Radioelektronika (RADIOELEKTRONIKA);2024-04-17

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