Wideband Speech

Wideband speech processing aims to enhance the quality and clarity of speech signals by expanding their frequency range, improving intelligibility and naturalness in applications like telephony and speech recognition. Current research heavily utilizes generative adversarial networks (GANs), often employing convolutional neural networks (CNNs) or U-Net architectures, to achieve high-fidelity bandwidth expansion and efficient waveform generation, sometimes incorporating parallel amplitude and phase prediction for improved results. These advancements are significant for improving the performance of various speech technologies and offer potential for real-time applications, particularly in scenarios with bandwidth limitations or noisy environments.