4 papers
Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe
Gaofei Shen, Martijn Bentum, Tom Lentz +2
Probing is widely used to study which features can be decoded from language model representations. However, the common decoding probe approach has two limitations that we aim to so…
Tracking the emergence of linguistic structure in self-supervised models learning from speech
Marianne de Heer Kloots, Martijn Bentum, Hosein Mohebbi +3
Self-supervised speech models learn effective representations of spoken language, which have been shown to reflect various aspects of linguistic structure. But when does such struc…
What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training
Marianne de Heer Kloots, Hosein Mohebbi, Charlotte Pouw +3
How language-specific are speech representations learned by self-supervised models? Existing work has shown that a range of linguistic features can be successfully decoded from end…
Word stress in self-supervised speech models: A cross-linguistic comparison
Martijn Bentum, Louis ten Bosch, Tomas O. Lentz
In this paper we study word stress representations learned by self-supervised speech models (S3M), specifically the Wav2vec 2.0 model. We investigate the S3M representations of wor…