5 papers · 1 filter
In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Heads
Charlotte Pouw, Hosein Mohebbi, Afra Alishahi +1
In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we investigate how linguistic and ac…
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…
A Linguistically Motivated Analysis of Intonational Phrasing in Text-to-Speech Systems: Revealing Gaps in Syntactic Sensitivity
Charlotte Pouw, Afra Alishahi, Willem Zuidema
We analyze the syntactic sensitivity of Text-to-Speech (TTS) systems using methods inspired by psycholinguistic research. Specifically, we focus on the generation of intonational p…
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…
Perception of Phonological Assimilation by Neural Speech Recognition Models
Charlotte Pouw, Marianne de Heer Kloots, Afra Alishahi +1
Human listeners effortlessly compensate for phonological changes during speech perception, often unconsciously inferring the intended sounds. For example, listeners infer the under…