Audio Segmentation

Audio segmentation, the task of dividing audio streams into meaningful segments, is crucial for various applications like speech translation and sound event detection. Current research emphasizes developing accurate and efficient segmentation models, focusing on lightweight architectures like those incorporating convolutional neural networks and dynamic time warping, as well as explainable models based on non-negative matrix factorization to improve transparency and trustworthiness. These advancements aim to improve the performance of downstream tasks and address the need for robust, interpretable, and computationally efficient solutions for real-world applications ranging from manufacturing quality control to speech-to-text translation.