Listening Test

Listening tests assess the perceptual quality and intelligibility of audio signals, crucial for evaluating speech processing systems and assessing auditory comprehension. Current research focuses on developing accurate and efficient prediction models, often employing deep neural networks like convolutional and recurrent architectures, to replace or supplement time-consuming human listening tests, leveraging techniques such as self-supervised learning and multi-task learning. These advancements aim to improve the speed and cost-effectiveness of audio quality assessment, impacting fields ranging from speech synthesis and noise reduction to language assessment and hearing aid development.