5 citations · 5 across the 3 of their papers we have counts for
3 papers
On Using Distribution-Based Compositionality Assessment to Evaluate Compositional Generalisation in Machine Translation
Anssi Moisio, Mathias Creutz, Mikko Kurimo
Compositional generalisation (CG), in NLP and in machine learning more generally, has been assessed mostly using artificial datasets. It is important to develop benchmarks to asses…
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference
Dejan Porjazovski, Yaroslav Getman, Tamás Grósz +1
Large pre-trained models are essential in paralinguistic systems, demonstrating effectiveness in tasks like emotion recognition and stuttering detection. In this paper, we employ l…
Comparison and Analysis of New Curriculum Criteria for End-to-End ASR
Georgios Karakasidis, Tamás Grósz, Mikko Kurimo
It is common knowledge that the quantity and quality of the training data play a significant role in the creation of a good machine learning model. In this paper, we take it one st…