2 papers
cs.CL2021
Multilingual transfer of acoustic word embeddings improves when training on languages related to the target zero-resource language
Christiaan Jacobs, Herman Kamper
Acoustic word embedding models map variable duration speech segments to fixed dimensional vectors, enabling efficient speech search and discovery. Previous work explored how embedd…
cs.CL2021
Acoustic word embeddings for zero-resource languages using self-supervised contrastive learning and multilingual adaptation
Christiaan Jacobs, Yevgen Matusevych, Herman Kamper
Acoustic word embeddings (AWEs) are fixed-dimensional representations of variable-length speech segments. For zero-resource languages where labelled data is not available, one AWE…