3 papers
cs.CL2022
Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings
Badr M. Abdullah, Bernd Möbius, Dietrich Klakow
Models of acoustic word embeddings (AWEs) learn to map variable-length spoken word segments onto fixed-dimensionality vector representations such that different acoustic exemplars…
cs.CL2021
How Familiar Does That Sound? Cross-Lingual Representational Similarity Analysis of Acoustic Word Embeddings
Badr M. Abdullah, Iuliia Zaitova, Tania Avgustinova +2
How do neural networks "perceive" speech sounds from unknown languages? Does the typological similarity between the model's training language (L1) and an unknown language (L2) have…
cs.CL2021
Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Study
Badr M. Abdullah, Marius Mosbach, Iuliia Zaitova +2
Several variants of deep neural networks have been successfully employed for building parametric models that project variable-duration spoken word segments onto fixed-size vector r…