ROMPAR: Morphological Completion and Demographic Unlearning for Romanian-Accented Speech Recognition
Automated transcription of parliamentary proceedings faces significant hurdles due to demographic bias, dialectal variation, and technical artifacts such as utterance truncation during segmentation. This paper introduces the ROManian PARliamentary Speech Corpus (ROMPAR) dataset, a 17.80-hour corpus of Romanian and Moldavian parliamentary speech, featuring double-annotated ground truth and explicit labels for reconstructed word fragments. To build a robust ASR system, we propose a multi-task adversarial training framework that enforces demographic invariance across age, gender, and dialect. We address the inherent instability of adversarial objectives in generative architectures by introdu...
| Authors | Andrei-Marius Avram, Aureliu-Valentin Antonie, Ştefan-Bogdan Badea et al. |
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| Primary category | cs.CL |
| Published | 14 June 2026 |
| Last updated at source | 14 June 2026 |
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