2 citations · 4 across the 4 of their papers we have counts for
7 papers
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…
A phonetic model of non-native spoken word processing
Yevgen Matusevych, Herman Kamper, Thomas Schatz +2
Non-native speakers show difficulties with spoken word processing. Many studies attribute these difficulties to imprecise phonological encoding of words in the lexical memory. We t…
Evaluating computational models of infant phonetic learning across languages
Yevgen Matusevych, Thomas Schatz, Herman Kamper +2
In the first year of life, infants' speech perception becomes attuned to the sounds of their native language. Many accounts of this early phonetic learning exist, but computational…
Improved acoustic word embeddings for zero-resource languages using multilingual transfer
Herman Kamper, Yevgen Matusevych, Sharon Goldwater
Acoustic word embeddings are fixed-dimensional representations of variable-length speech segments. Such embeddings can form the basis for speech search, indexing and discovery syst…
Analyzing autoencoder-based acoustic word embeddings
Yevgen Matusevych, Herman Kamper, Sharon Goldwater
Recent studies have introduced methods for learning acoustic word embeddings (AWEs)---fixed-size vector representations of words which encode their acoustic features. Despite the w…
Multilingual acoustic word embedding models for processing zero-resource languages
Herman Kamper, Yevgen Matusevych, Sharon Goldwater
Acoustic word embeddings are fixed-dimensional representations of variable-length speech segments. In settings where unlabelled speech is the only available resource, such embeddin…