Abstract
This paper presents Instituto de Telecomunicações’s submission to the IWSLT 2025 Shared Task on Instruction Following Speech Processing. We submit results for the Short Track, i.e., speech recognition, translation, and spoken question answering. Our model is a unified speech-to-text model that integrates a pretrained continuous speech encoder and text decoder through a first phase of modality alignment and a second phase of instruction fine-tuning. Crucially, we focus on using small-scale language model backbones (< 2B) and restrict to high-quality, CC-BY data along with synthetic data generation to supplement existing resources.
Cite
CITATION STYLE
Attanasio, G., Sannigrahi, S., Peters, B., & Martins, A. F. T. (2025). Instituto de Telecomunicações at IWSLT 2025: Aligning Small-Scale Speech and Language Models for Speech-to-Text Learning. In IWSLT 2025 - 22nd International Conference on Spoken Language Translation, Proceedings of the Conference (pp. 347–353). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.iwslt-1.36
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