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# ICASSP-2024-Papers | ||
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<table> | ||
<tr> | ||
<td><strong>Application</strong></td> | ||
<td> | ||
<a href="https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers" style="float:left;"> | ||
<img src="https://img.shields.io/badge/🤗-NewEraAI--Papers-FFD21F.svg" alt="App" /> | ||
</a> | ||
</td> | ||
</tr> | ||
<tr> | ||
<td><strong>Previous Collections</strong></td> | ||
<td> | ||
<a href="https://github.com/DmitryRyumin/ICASSP-2023-24-Papers/blob/main/README_2023.md"> | ||
<img src="http://img.shields.io/badge/ICASSP-2023-0073AE.svg" alt="Conference"> | ||
</a> | ||
</td> | ||
</tr> | ||
</table> | ||
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<div align="center"> | ||
<a href="https://github.com/DmitryRyumin/ICASSP-2023-24-Papers/blob/main/sections/2024/main/MLSP-P22.md"> | ||
<img src="https://cdn.jsdelivr.net/gh/DmitryRyumin/NewEraAI-Papers@main/images/left.svg" width="40" alt="" /> | ||
</a> | ||
<a href="https://github.com/DmitryRyumin/ICASSP-2023-24-Papers/"> | ||
<img src="https://cdn.jsdelivr.net/gh/DmitryRyumin/NewEraAI-Papers@main/images/home.svg" width="40" alt="" /> | ||
</a> | ||
<a href="https://github.com/DmitryRyumin/ICASSP-2023-24-Papers/blob/main/sections/2024/main/MLSP-P23.md"> | ||
<img src="https://cdn.jsdelivr.net/gh/DmitryRyumin/NewEraAI-Papers@main/images/right.svg" width="40" alt="" /> | ||
</a> | ||
</div> | ||
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## Speaker Recognition and Anonymization | ||
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![Section Papers](https://img.shields.io/badge/Section%20Papers-12-42BA16) ![Preprint Papers](https://img.shields.io/badge/Preprint%20Papers-2-b31b1b) ![Papers with Open Code](https://img.shields.io/badge/Papers%20with%20Open%20Code-0-1D7FBF) ![Papers with Video](https://img.shields.io/badge/Papers%20with%20Video-0-FF0000) | ||
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| **Title** | **Repo** | **Paper** | **Video** | | ||
|-----------|:--------:|:---------:|:---------:| | ||
| Multi-View Speaker Embedding Learning for Enhanced Stability and Discriminability | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10448494-E4A42C.svg)](https://ieeexplore.ieee.org/document/10448494) | :heavy_minus_sign: | | ||
| What Do Self-Supervised Speech and Speaker Models Learn? New Findings From a Cross Model Layer-Wise Analysis | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10446422-E4A42C.svg)](https://ieeexplore.ieee.org/document/10446422) <br/> [![arXiv](https://img.shields.io/badge/arXiv-2401.17632-b31b1b.svg)](https://arxiv.org/abs/2401.17632) | :heavy_minus_sign: | | ||
| A Speaker Recognition Method Based on Stable Learning | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10446329-E4A42C.svg)](https://ieeexplore.ieee.org/document/10446329) | :heavy_minus_sign: | | ||
| Generating High-Quality Adversarial Examples with Universal Perturbation-Based Adaptive Network and Improved Perceptual Loss | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10446184-E4A42C.svg)](https://ieeexplore.ieee.org/document/10446184) | :heavy_minus_sign: | | ||
| A Study on Graph Embedding for Speaker Recognition | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10448308-E4A42C.svg)](https://ieeexplore.ieee.org/document/10448308) | :heavy_minus_sign: | | ||
| Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models | :heavy_minus_sign: | [![IEEE Xplore](https://img.shields.io/badge/IEEE-10447161-E4A42C.svg)](https://ieeexplore.ieee.org/document/10447161) <br/> [![arXiv](https://img.shields.io/badge/arXiv-2401.12440-b31b1b.svg)](https://arxiv.org/abs/2401.12440) | :heavy_minus_sign: | |