Review - Speech processing Universal Performance Benchmark Review

The "SUPERB: Speech processing Universal PERformance Benchmark Review" paper introduces a comprehensive framework for measuring the performance of pre-trained models on various speech tasks, filling a gap in the development of such models. It categorizes speech tasks into content-based, speaker-based, semantic-based, and paralinguistics-based tasks. The paper also compares HuBERT Large and Wav2Vec2.0 Large models trained on librilight and librispeech datasets, with HuBERT Large outperforming the latter in eight of twelve tasks. This framework will likely drive research in representation learning and general speech processing.