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LIA and ELYADATA systems for the IWSLT 2025 low-resource speech translation shared task

Domaine:

natural language processing

Type de record:

paper
Créateur:
CheEllIstFor
Éditeur:
LunLabElyAvi
Éditeur:
CCSDAss
Hôte:avatar
International audience

In this paper, we present the approach and system setup of our participation in the IWSLT 2025 low-resource speech translation shared task. We submitted systems for three language pairs, namely Tunisian Arabic to English, North Levantine Arabic to English, and Fongbé to French. Both pipeline and end-to-end speech translation systems were explored for Tunisian Arabic to English and Fongbé to French pairs. However, only pipeline approaches were investigated for the North Levantine Arabic-English translation direction. All our submissions are based on the usage of pre-trained models that we further fine-tune with the shared task training data.

Visit

hal.science

Tasks

speech translationspeech processingmachine translation

Languages

Arabic, Tunisian Spoken

Tags

[INFO]Computer Science [cs]

Licenses

https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/OpenAccess

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