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20182022
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cs.CL2022

BPE vs. Morphological Segmentation: A Case Study on Machine Translation of Four Polysynthetic Languages

Manuel Mager, Arturo Oncevay, Elisabeth Mager +2

Morphologically-rich polysynthetic languages present a challenge for NLP systems due to data sparsity, and a common strategy to handle this issue is to apply subword segmentation.…

cs.CL2021

IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task

Pavel Denisov, Manuel Mager, Ngoc Thang Vu

This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team. We utilize state-of-the-art models combined with several data augment…

cs.CL2020

Tackling the Low-resource Challenge for Canonical Segmentation

Manuel Mager, Özlem Çetinoğlu, Katharina Kann

Canonical morphological segmentation consists of dividing words into their standardized morphemes. Here, we are interested in approaches for the task when training data is limited.…

cs.CL2020

GPT-too: A language-model-first approach for AMR-to-text generation

Manuel Mager, Ramon Fernandez Astudillo, Tahira Naseem +4

Meaning Representations (AMRs) are broad-coverage sentence-level semantic graphs. Existing approaches to generating text from AMR have focused on training sequence-to-sequence or g…

cs.CL2020

The IMS-CUBoulder System for the SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion

Manuel Mager, Katharina Kann

In this paper, we present the systems of the University of Stuttgart IMS and the University of Colorado Boulder (IMS-CUBoulder) for SIGMORPHON 2020 Task 2 on unsupervised morpholog…

cs.CL2019

Subword-Level Language Identification for Intra-Word Code-Switching

Manuel Mager, Özlem Çetinoğlu, Katharina Kann

Language identification for code-switching (CS), the phenomenon of alternating between two or more languages in conversations, has traditionally been approached under the assumptio…