WitrynaAbstract—Generative adversarial networks (GAN) have re- cently been shown to be efficient for speech enhancement. Most, if not all, existing speech enhancement … WitrynaSimilar to SEGAN, the generators are based on fully convolutional architecture and receive raw speech waveforms to accomplish speech enhancement: The project is …

Exploring Speech Enhancement with Generative Adversarial Networks …

Witryna13 maj 2024 · Self-Attention Generative Adversarial Network for Speech Enhancement Abstract: Existing generative adversarial networks (GANs) for speech enhancement … Witryna8 kwi 2024 · The discrepancy between the cost function used for training a speech enhancement model and human auditory perception usually makes the quality of enhanced speech unsatisfactory. Objective evaluation metrics which consider human perception can hence serve as a bridge to reduce the gap. trump: what\u0027s the deal

On Adversarial Training and Loss Functions for Speech …

Witryna1 kwi 2024 · Speech enhancement aims to improve the quality and intelligibility of speech signals, which is a challenging task in adverse environments. Speech enhancement generative adversarial network (SEGAN) that adopted a generative adversarial network (GAN) for speech enhancement achieved promising results. Witryna6 wrz 2024 · The SE cGAN consists of two networks, trained in an adversarial manner: a generator that tries to enhance the input noisy spectrogram, and a discriminator that tries to distinguish between enhanced spectrograms provided by the generator and clean ones from the database using the noisy spectrogram as a condition. Witryna[31] Phan H., et al., Improving gans for speech enhancement, IEEE Signal Process. Lett. 27 (2024) 1700 – 1704. Google Scholar [32] Zhang Z., et al., On loss functions and recurrency training for gan-based speech enhancement systems, 2024, arXiv preprint arXiv:2007.14974. Google Scholar trump wharton grades