Papers by Sarah Ebling
SwissADT: An Audio Description Translation System for Swiss Languages (2025.naacl-industry)
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| Challenge: | despite advances in multilingual machine translation, lack of well-crafted AD data impedes development of audio description translation systems. |
| Approach: | They propose an audio description translation system for three main Swiss languages and English . they combine human expertise with the power of Large Language Models to improve quality . |
| Outcome: | The proposed system is designed to enhance accessibility for multilingual populations in Switzerland. |
Machine Translation between Spoken Languages and Signed Languages Represented in SignWriting (2023.findings-eacl)
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| Challenge: | Yin et al. ( 2021) calls for including sign language processing (SLP) in natural language processing research. |
| Approach: | They propose to use a sign language writing system to parse, factorize, decode and evaluate signed languages. |
| Outcome: | The proposed method achieves over 30 BLEU in a bilingual setup and over 20 BLUE in two multilingual setups. |
A Corpus for Automatic Readability Assessment and Text Simplification of German (2020.lrec-1)
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| Challenge: | Using monolingual-only data, we can automate readability assessment and text simplification of simplified language. |
| Approach: | They present a corpus for automatic readability assessment and automatic text simplification for German using parallel and monolingual data. |
| Outcome: | The proposed corpus is compiled from web sources and contains information on text structure, typography, font style, and images. |
Considerations for meaningful sign language machine translation based on glosses (2023.acl-short)
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| Challenge: | In machine translation, sign language translation based on glosses is becoming more popular . limitations of glossed approaches are not discussed in a transparent manner, and there is no common standard for evaluation. |
| Approach: | They propose to use a gloss-based approach to evaluate machine translation results . they propose to include realistic datasets, stronger baselines and convincing evaluation . |
| Outcome: | The proposed approach is based on a neural gloss translation model. |
Segment, Embed, and Align: A Universal Recipe for Aligning Subtitles to Signing (2026.acl-long)
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| Challenge: | Existing approaches for aligning spoken language text to sign language videos rely on end-to-end training tied to a specific language or dataset. |
| Approach: | They propose a universal approach for aligning spoken language text with corresponding timestamps to sign language videos using a lightweight dynamic programming procedure. |
| Outcome: | The proposed method can be used on four sign language datasets and is highly efficient on CPU. |
SwissSLi: The Multi-parallel Sign Language Corpus for Switzerland (2024.lrec-main)
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| Challenge: | Using a CC BY-NC-SA 4.0 license, this corpus contains parallel sign language videos and spoken language subtitles. |
| Approach: | They introduce SwissSLi, the first sign language corpus that contains parallel data of all three Swiss sign languages. |
| Outcome: | The proposed corpus contains parallel sign language videos and spoken language subtitles. |
Audio Description Generation in the Era of LLMs and VLMs: A Review of Transferable Generative AI Technologies (2025.findings-naacl)
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| Challenge: | Audio descriptions (ADs) are acoustic commentaries designed to assist blind and visually impaired individuals in accessing digital media content. |
| Approach: | They examine how state-of-the-art NLP and CV technologies can be applied to generate ADs . they identify essential research directions for the future . |
| Outcome: | The proposed technologies can be applied to generate audio descriptions (ADs) the process is time-consuming and costly, and requires significant human effort . the authors identify key research directions for the future . |
SignCLIP: Connecting Text and Sign Language by Contrastive Learning (2024.emnlp-main)
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| Challenge: | SignCLIP is an efficient method of learning useful visual representations for sign language processing from large-scale, multilingual video-text pairs without optimizing for a specific task or sign language of limited size. |
| Approach: | They propose a method for learning visual representations for sign language processing from large-scale video-text pairs without directly optimizing for a specific task or sign language. |
| Outcome: | The proposed model can learn from multilingual video-text pairs without optimizing for a specific task or sign language of limited size. |
SMILE Swiss German Sign Language Dataset (L18-1)
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Sarah Ebling, Necati Cihan Camgöz, Penny Boyes Braem, Katja Tissi, Sandra Sidler-Miserez, Stephanie Stoll, Simon Hadfield, Tobias Haug, Richard Bowden, Sandrine Tornay, Marzieh Razavi, Mathew Magimai-Doss
| Challenge: | The goal of an ongoing three-year project in Switzerland is to pioneer an assessment system for lexical signs of Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS) that relies on sign language recognition. |
| Approach: | The goal of the project is to pioneer an assessment system for lexical signs of Swiss German Sign Language that relies on sign language recognition. |
| Outcome: | The system will give adult L2 learners of DSGS feedback on the correctness of the manual parameters (handshape, hand position, location, and movement) of isolated signs they produce. |
Linguistically Motivated Sign Language Segmentation (2023.findings-emnlp)
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| Challenge: | Sign language segmentation is a crucial task in sign language processing systems. |
| Approach: | They propose to combine two kinds of segmentation: segmentation into individual signs and segmentation to segment into phrases, larger units comprising several signs. |
| Outcome: | The proposed model is based on linguistic cues observed in sign language corpora and replaces the predominant IO tagging scheme with BIO taging to account for continuous signing. |