Scholar
Dan Oneață
Google Scholar ID: NX-38C0AAAAJ
University Politehnica of Bucharest
Citations & Impact
Citations
689
H-index
12
i10-index
17
Publications
20
Co-authors
7
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - Publications:
- - 'Seeing what tastes good: Revisiting multimodal distributional semantics in the billion parameter era', Findings of the Annual Meeting of the Association for Computational Linguistics, 2025
- - 'The mutual exclusivity bias of bilingual visually grounded speech models', Interspeech, 2025
- - 'Circumventing shortcuts in audio-visual deepfake detection datasets with unsupervised learning', IEEE Conference on Computer Vision and Pattern Recognition, 2025
- - 'Easy, interpretable, effective: openSMILE for voice deepfake detection', IEEE International Conference on Acoustics, Speech, and Signal Processing, 2025
- - 'Translating speech with just images', Interspeech, 2024
- - 'Towards generalisable and calibrated synthetic speech detection with self-supervised representations', Interspeech, 2024
- - 'Visually grounded speech models have a mutual exclusivity bias', Transactions of the Association for Computational Linguistics, 2024
- - 'Visually grounded few-shot word learning in low-resource settings', IEEE/ACM Transactions on Audio, Speech, and Language, 2024
- - 'Multilingual multimodal learning with machine translated text', Findings of Empirical Methods in Natural Language Processing, 2022
- - 'Keyword localisation in untranscribed speech using visually grounded speech models', IEEE Journal of Selected Topics in Signal Processing, 2022
- - 'Improving multimodal speech recognition by data augmentation and speech representations', IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2022
- - 'Multimodal speech recognition for unmanned aerial vehicles', Computers & Electrical Engineering, 2021
- - 'An evaluation of word-level confidence estimation for end-to-end automatic speech recognition', IEEE Spoken Language Technology, 2021
- - 'Data-filtering methods for self-training of automatic speech recognition'
Research Experience
- - Research Scientist at the SpeeD lab, University Politehnica of Bucharest.
- - Previously worked in the industry at Fordaq and Eloquentix.
Education
- - PhD in Computer Vision and Machine Learning from Université Grenoble Alpes, supervised by Cordelia Schmid and Jakob Verbeek.
- - MSc in Artificial Intelligence from the University of Edinburgh, dissertation under Iain Murray.
Background
- - Research interests include general machine learning techniques and their applications to computer vision, speech, and natural language processing.
- - Enjoys reading about category theory and its applications.
