2024
Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio
ICASSP 2024accepted
Although transformer-based models have improved the state-of-the-art in speech recognition, it is still not well understood what information from the speech signal these models encode in their latent representations. This study investigates the potential of using labelled data (TIMIT) to probe wav2v…