GAN-Based Speech Enhancement for Low SNR Using Latent Feature Conditioning
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866912075444387840 |
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| author | Shetu, Shrishti Saha Habets, Emanuël A. P. Brendel, Andreas |
| author_facet | Shetu, Shrishti Saha Habets, Emanuël A. P. Brendel, Andreas |
| contents | Enhancing speech quality under adverse SNR conditions remains a significant challenge for discriminative deep neural network (DNN)-based approaches. In this work, we propose DisCoGAN, which is a time-frequency-domain generative adversarial network (GAN) conditioned by the latent features of a discriminative model pre-trained for speech enhancement in low SNR scenarios. Our proposed method achieves superior performance compared to state-of-the-arts discriminative methods and also surpasses end-to-end (E2E) trained GAN models. We also investigate the impact of various configurations for conditioning the proposed GAN model with the discriminative model and assess their influence on enhancing speech quality |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_13599 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GAN-Based Speech Enhancement for Low SNR Using Latent Feature Conditioning Shetu, Shrishti Saha Habets, Emanuël A. P. Brendel, Andreas Audio and Speech Processing Sound Signal Processing Enhancing speech quality under adverse SNR conditions remains a significant challenge for discriminative deep neural network (DNN)-based approaches. In this work, we propose DisCoGAN, which is a time-frequency-domain generative adversarial network (GAN) conditioned by the latent features of a discriminative model pre-trained for speech enhancement in low SNR scenarios. Our proposed method achieves superior performance compared to state-of-the-arts discriminative methods and also surpasses end-to-end (E2E) trained GAN models. We also investigate the impact of various configurations for conditioning the proposed GAN model with the discriminative model and assess their influence on enhancing speech quality |
| title | GAN-Based Speech Enhancement for Low SNR Using Latent Feature Conditioning |
| topic | Audio and Speech Processing Sound Signal Processing |
| url | https://arxiv.org/abs/2410.13599 |