2 citations · 4 across the 12 of their papers we have counts for
14 papers
CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions
Francesca Padovani, Xiulin Yang, Bastian Bunzeck +4
CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Leveraging the recent release of t…
Is Child-Directed Language Optimized for Word Learning? A Computational Study of Verb Meaning Acquisition
Francesca Padovani, Jaap Jumelet, Yevgen Matusevych +1
Is child-directed language (CDL) optimized to support language learning, and which aspects of linguistic development does it facilitate? We investigate this question using neural l…
The mutual exclusivity bias of bilingual visually grounded speech models
Dan Oneata, Leanne Nortje, Yevgen Matusevych +1
Mutual exclusivity (ME) is a strategy where a novel word is associated with a novel object rather than a familiar one, facilitating language learning in children. Recent work has f…
Child-Directed Language Does Not Consistently Boost Syntax Learning in Language Models
Francesca Padovani, Jaap Jumelet, Yevgen Matusevych +1
Seminal work by Huebner et al. (2021) showed that language models (LMs) trained on English Child-Directed Language (CDL) can reach similar syntactic abilities as LMs trained on muc…
Generating Completions for Broca's Aphasic Sentences Using Large Language Models
Sijbren van Vaals, Yevgen Matusevych, Frank Tsiwah
Broca's aphasia is a type of aphasia characterized by non-fluent, effortful and agrammatic speech production with relatively good comprehension. Since traditional aphasia treatment…
Choosy Babies Need One Coach: Inducing Mode-Seeking Behavior in BabyLlama with Reverse KL Divergence
Shaozhen Shi, Yevgen Matusevych, Malvina Nissim
This study presents our submission to the Strict-Small Track of the 2nd BabyLM Challenge. We use a teacher-student distillation setup with the BabyLLaMa model (Timiryasov and Taste…
Visually Grounded Speech Models have a Mutual Exclusivity Bias
Leanne Nortje, Dan Oneaţă, Yevgen Matusevych +1
When children learn new words, they employ constraints such as the mutual exclusivity (ME) bias: a novel word is mapped to a novel object rather than a familiar one. This bias has…
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…
Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection
Maria Corkery, Yevgen Matusevych, Sharon Goldwater
The cognitive mechanisms needed to account for the English past tense have long been a subject of debate in linguistics and cognitive science. Neural network models were proposed e…