Inverse Short Time Fourier Transform

The inverse short-time Fourier transform (iSTFT) is a signal processing technique increasingly used to improve the efficiency and speed of various machine learning models, particularly in audio and image processing. Current research focuses on integrating iSTFT into neural network architectures, such as replacing computationally expensive components in vocoders and leveraging its properties for parameter-efficient fine-tuning of large language models and improved medical image segmentation. This approach offers significant advantages in terms of reduced computational cost and faster inference times, leading to more efficient and potentially real-time applications in speech synthesis, medical imaging, and other fields.