9 citations · 18 across the 7 of their papers we have counts for
16 papers
On the reliability of feature attribution methods for speech classification
Gaofei Shen, Hosein Mohebbi, Arianna Bisazza +2
As the capabilities of large-scale pre-trained models evolve, understanding the determinants of their outputs becomes more important. Feature attribution aims to reveal which parts…
Co-creation for Sign Language Processing and Machine Translation
Lisa Lepp, Dimitar Shterionov, Mirella De Sisto +1
Sign language machine translation (SLMT) -- the task of automatically translating between sign and spoken languages or between sign languages -- is a complex task within the field…
QE4PE: Word-level Quality Estimation for Human Post-Editing
Gabriele Sarti, Vilém Zouhar, Grzegorz Chrupała +3
Word-level quality estimation (QE) methods aim to detect erroneous spans in machine translations, which can direct and facilitate human post-editing. While the accuracy of word-lev…
Disentangling Textual and Acoustic Features of Neural Speech Representations
Hosein Mohebbi, Grzegorz Chrupała, Willem Zuidema +2
Neural speech models build deeply entangled internal representations, which capture a variety of features (e.g., fundamental frequency, loudness, syntactic category, or semantic co…
Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations
Chris Emmery, Ákos Kádár, Grzegorz Chrupała +1
A limited amount of studies investigates the role of model-agnostic adversarial behavior in toxic content classification. As toxicity classifiers predominantly rely on lexical cues…
ZR-2021VG: Zero-Resource Speech Challenge, Visually-Grounded Language Modelling track, 2021 edition
Afra Alishahi, Grzegorz Chrupała, Alejandrina Cristia +5
We present the visually-grounded language modelling track that was introduced in the Zero-Resource Speech challenge, 2021 edition, 2nd round. We motivate the new track and discuss…