1 citations · 3 across the 7 of their papers we have counts for
8 papers
Automatically assessing oral narratives of Afrikaans and isiXhosa children
Retief Louw, Emma Sharratt, Febe de Wet +3
Developing narrative and comprehension skills in early childhood is critical for later literacy. However, teachers in large preschool classrooms struggle to accurately identify stu…
Low-resource keyword spotting using contrastively trained transformer acoustic word embeddings
Julian Herreilers, Christiaan Jacobs, Thomas Niesler
We introduce a new approach, the ContrastiveTransformer, that produces acoustic word embeddings (AWEs) for the purpose of very low-resource keyword spotting. The ContrastiveTransfo…
Speech Recognition for Automatically Assessing Afrikaans and isiXhosa Preschool Oral Narratives
Christiaan Jacobs, Annelien Smith, Daleen Klop +3
We develop automatic speech recognition (ASR) systems for stories told by Afrikaans and isiXhosa preschool children. Oral narratives provide a way to assess children's language dev…
Multilingual acoustic word embeddings for zero-resource languages
Christiaan Jacobs
This research addresses the challenge of developing speech applications for zero-resource languages that lack labelled data. It specifically uses acoustic word embedding (AWE) -- f…
Leveraging multilingual transfer for unsupervised semantic acoustic word embeddings
Christiaan Jacobs, Herman Kamper
Acoustic word embeddings (AWEs) are fixed-dimensional vector representations of speech segments that encode phonetic content so that different realisations of the same word have si…
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili
Christiaan Jacobs, Nathanaël Carraz Rakotonirina, Everlyn Asiko Chimoto +2
We consider hate speech detection through keyword spotting on radio broadcasts. One approach is to build an automatic speech recognition (ASR) system for the target low-resource la…
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…
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…