Objective Intelligibility Prediction Using Distance Metrics on Speech Foundation Model Representations

High-dimensional representations of pretrained speech foundation models have proven beneficial for objective speech quality and intelligibility prediction. While existing work on neural intelligibility prediction usually leverages such representations for task-specific fine-tuning, in this work we e