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Supervised Speech Enhancement with Self-Attention

28 minute read

Published:

This article introduces a Deep Generative Speech Enhancement model that utilizes a hybrid architecture combining U-Net and Transformer models. The model is trained in a supervized manner to remove various types of noise from audio signals, enhancing the clarity and quality of speech. We have tested the model on several noise conditions, demonstrating its effectiveness across different environments.

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publications

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.