Papers with SLT
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation (L18-1)
Copied to clipboard
| Challenge: | Recent work in spoken language translation (SLT) has attempted to build end-to-end speech-totext translation without using source language transcription during learning or decoding. |
| Approach: | They propose to augment an existing (monolingual) corpus: LibriSpeech. |
| Outcome: | The proposed corpus is derived from read audiobooks from the LibriVox project and has been carefully segmented and aligned. |
SLTEV: Comprehensive Evaluation of Spoken Language Translation (2021.eacl-demos)
Copied to clipboard
| Challenge: | Spoken Language Translation (SLT) evaluation of machine translation (MT) quality has been investigated for decades. |
| Approach: | They propose an open-source tool for assessing machine translation (MT) quality based on time-stamped transcripts and reference translations. |
| Outcome: | The proposed evaluation tool is based on time-stamped transcripts and reference translations into a target language. |
Adaptive Simultaneous Sign Language Translation with Confident Translation Length Estimation (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing non-simultaneous sign language translation methods suffer from inherent inference delays in real-time scenarios. |
| Approach: | They propose an adaptive policy for simultaneous sign language translation that progressively converts incrementally received sign video into its corresponding natural sentence. |
| Outcome: | The proposed policy excels in situations requiring extremely low latency. |
Sign Language Translation with Sentence Embedding Supervision (2024.acl-short)
Copied to clipboard
| Challenge: | State-of-the-art sign language translation systems facilitate learning through gloss annotations when available at scale. |
| Approach: | They propose to use sentence embeddings of the target sentences at training time that take the role of glosses to supervise the learning process. |
| Outcome: | The proposed method significantly outperforms gloss-free approaches on German and American sign languages and with mono- and multilingual sentence embeddings and translation systems. |
Multilingual Gloss-free Sign Language Translation: Towards Building a Sign Language Foundation Model (2025.acl-short)
Copied to clipboard
| Challenge: | Existing studies focus on translating a single SL into a spoken language (one-to-one SLT) however, multilingual SLT remains unexplored due to language conflicts and alignment difficulties across SLs and spoken languages. |
| Approach: | They propose a multilingual gloss-free model that can be used to translate a single SL into a spoken language and generate a token-level SL identification and spoken text. |
| Outcome: | The proposed model supports 10 SLs and handles one-to-one, many-to-1, and many- to-many SLT tasks. |
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News (2024.lrec-main)
Copied to clipboard
| Challenge: | a new dataset is being developed to enrich resources for sign language research . the dataset is 16.07 hours of sign videos of two signers with a vocabulary of 6,515 glosses and 2,850 Chinese characters or 18K Chinese words. |
| Approach: | They introduce a new Hong Kong sign language dataset called TVB-HKSL-News . the dataset is collected from a TV news program and contains sign videos . they aim to support research in sign language recognition and translation . |
| Outcome: | The proposed dataset supports sign language recognition and translation research in Hong Kong . it consists of 16.07 hours of sign videos of two signers with a vocabulary of 6,515 glosses and 2,850 Chinese characters or 18K Chinese words . |
Signer Diversity-driven Data Augmentation for Signer-Independent Sign Language Translation (2024.findings-naacl)
Copied to clipboard
| Challenge: | Existing methods for sign language translation (SLT) rely on signer identity labels, which is often impractical and costly in real-world applications. |
| Approach: | They propose a signer diversity-driven data augmentation method that can generalize to signers not encountered during training. |
| Outcome: | The proposed method achieves state-of-the-art results without relying on signer identity labels. |
Sign Language Production With Avatar Layering: A Critical Use Case over Rare Words (2022.lrec-1)
Copied to clipboard
| Challenge: | Existing vision-based sign language production approaches suffer from out-of-vocabulary (OOV) and test-time generalization problems. |
| Approach: | They propose an avatar-based sign language production system that generates sign language videos from spoken language expressions. |
| Outcome: | The proposed system achieves higher BLEU-4 and higher ROUGE-L scores on a new Korean-Korean sign language dataset. |
An Efficient Gloss-Free Sign Language Translation Using Spatial Configurations and Motion Dynamics with LLMs (2025.naacl-long)
Copied to clipboard
| Challenge: | Existing methods for sign language translation rely on glosses, which are written representations of signs. |
| Approach: | They propose a new LLM-based SLT framework that uses off-the-shelf visual encoders to extract spatial and motion features from sign videos. |
| Outcome: | The proposed framework captures spatial configurations and motion dynamics in sign language without domain-specific tuning. |
MuST-C: a Multilingual Speech Translation Corpus (N19-1)
Copied to clipboard
| Challenge: | Current research on spoken language translation (SLT) has to confront the scarcity of sizeable and publicly available training corpora. |
| Approach: | They propose a multilingual speech translation corpus that will facilitate the training of end-to-end systems for SLT from English into 8 languages. |
| Outcome: | The proposed multilingual speech translation corpus will facilitate the training of end-to-end systems for spoken language translation from English into 8 languages. |
Improvement in Sign Language Translation Using Text CTC Alignment (2025.coling-main)
Copied to clipboard
| Challenge: | Current sign language translation (SLT) approaches rely on gloss-based supervision with Connectionist Temporal Classification (CTC) limiting their ability to handle non-monotonic alignments between sign language video and spoken text. |
| Approach: | They propose a method that integrates CTC/Attention with the attention mechanism during decoding and integrates it with the sign language video and spoken text. |
| Outcome: | The proposed method outperforms the pure-attention baseline and achieves comparable results to state-of-the-art methods. |
Improving Multilingual Sign Language Translation with Automatically Clustered Language Family Information (2025.coling-main)
Copied to clipboard
| Challenge: | Recent research has focused on bilingual translation models, but multilingual sign language translation presents unique challenges due to the diversity of sign languages across nations. |
| Approach: | They propose a method that leverages sign language families to improve MSLT performance. |
| Outcome: | The proposed approach can achieve balance between translation accuracy and computational cost by regulating the number of language families. |
Language Tags Matter for Zero-Shot Neural Machine Translation (2021.findings-acl)
Copied to clipboard
| Challenge: | Existing studies on multilingual machine translation have ignored the importance of LTs. |
| Approach: | They propose to use language tag (LT) strategies to indicate translation directions in MNMT to enhance consistency and alleviate off-target issues in zero-shot directions. |
| Outcome: | The proposed model could translate between unsupervised languages and achieve a +8 BLEU score difference over other LT strategies in translation tasks. |
Prior Knowledge and Memory Enriched Transformer for Sign Language Translation (2022.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for sign language translation do not explore all of them . visual and textual understanding and additional prior knowledge learning are challenging . |
| Approach: | They propose a method which integrates auxiliary information into vanilla transformer for SLT . they use visual-textual context information and additional auxiliary knowledge of a word . |
| Outcome: | The proposed method improves the understanding of sign language videos with visual and textual understanding and additional prior knowledge learning. |
Think in Latent Thoughts: A New Paradigm for Gloss-Free Sign Language Translation (2026.acl-long)
Copied to clipboard
| Challenge: | Existing approaches to sign language translation (SLT) assume video segments are directly mappable to spoken-language words. |
| Approach: | They propose a reasoning-driven SLT framework that uses an ordered sequence of latent thoughts as an explicit middle layer between video and generated text. |
| Outcome: | The proposed model improves coherence and faithfulness over existing gloss-free methods. |
Towards Privacy-Aware Sign Language Translation at Scale (2024.acl-long)
Copied to clipboard
| Challenge: | Existing sign language training systems require detailed and time aligned annotations to be effective. |
| Approach: | They propose a two-stage framework for privacy-aware SLT at scale that leverages self-supervised video pretraining on anonymized and unannotated videos followed by supervised SLT finetuning on a curated parallel dataset. |
| Outcome: | The proposed framework outperforms baselines on the How2Sign dataset and achieves state-of-the-art finetuned and zero-shot gloss-free SLT performance. |
Better Sign Language Translation with STMC-Transformer (2020.coling-main)
Copied to clipboard
| Challenge: | Current SLT approaches use a sign language recognition system to extract sign language glosses from videos. |
| Approach: | They propose to use a Sign Language Recognition system to extract sign language glosses from videos and a translation system to generate spoken language translations from the glossed sign language. |
| Outcome: | The proposed system outperforms existing methods on gloss-to-text and video-to text translations on the ASLG-PC12 corpus. |
Continual Learning in Multilingual Sign Language Translation (2025.naacl-long)
Copied to clipboard
| Challenge: | Despite the low translation quality of sign language, many machine learning approaches are still in its infancy. |
| Approach: | They propose to use continual learning for mul- tilingual SLT to improve translation quality. |
| Outcome: | The proposed methods outperform baseline and fine-tuning approaches in sign language translation. |
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation (2024.lrec-main)
Copied to clipboard
| Challenge: | Previous Sign Language Translation methods have relied on gloss annotations to improve performance, but labeling high-quality glosses is labor-intensive and inefficient. |
| Approach: | They propose to integrate Large Language Model (LLM) into SLT by factorizing learning into two stages to improve the learning curve. |
| Outcome: | The proposed approach improves on three SLT datasets conducted under the gloss-free setting. |
Gloss-Free End-to-End Sign Language Translation (2023.acl-long)
Copied to clipboard
| Challenge: | a study of sign language translation without gloss annotations focuses on the problem of gloss annotation . gloss annotation is hard to acquire, especially in large quantities, and limits the domain coverage of translation datasets . |
| Approach: | They propose a gloss-free end-to-end sign language translation framework to solve this problem . gloss annotations are hard to acquire, especially in large quantities, they argue . |
| Outcome: | The proposed framework improves sign language translation performance on large-scale datasets . gloss annotations are hard to acquire, especially in large quantities . |
Cross-modality Data Augmentation for End-to-End Sign Language Translation (2023.findings-emnlp)
Copied to clipboard
| Challenge: | End-to-end sign language translation (SLT) aims to convert sign language videos into spoken language texts without intermediate representations. |
| Approach: | They propose a cross-modality data-augmented framework to transfer gloss-to-text translation capabilities to end-to end sign language translation. |
| Outcome: | The proposed framework outperforms baseline models on two widely used SLT datasets. |
SAME: Signer-Aware Mixture-of-Experts for Test-Time Adaptation in Sign Language Translation (2026.acl-long)
Copied to clipboard
| Challenge: | Existing methods for supervised fine-tuning are limited due to labeled data . existing methods require long adaptation times and batch statistics are unavailable in streaming settings . |
| Approach: | They propose a plug-and-play, signer-aware Mixture-of-Experts (MoE) TTA architecture for SLT . they use a combination of lightweight MoE modules and unsupervised regularizers to decouple domain shift . |
| Outcome: | The proposed test-time adaptation outperforms existing TTA methods in sign language translation . the proposed architecture can be used in real-world deployments without labeling . |
Rethinking Sign Language Translation: The Impact of Signer Dependence on Model Evaluation (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Sign Language Translation evaluations remain largely signer-dependent, with overlapping signers across train/dev/test. |
| Approach: | We conduct signer-fold cross-validation on three leading SLT models . they find that under signer independent evaluation performance drops sharply . |
| Outcome: | a signer-dependent evaluation can substantially overestimate SLT capability, the authors say . they recommend adopting signer independent protocols to ensure generalisation to unseen signers . |
It’s Not a Walk in the Park! Challenges of Idiom Translation in Speech-to-text Systems (2025.acl-long)
Copied to clipboard
| Challenge: | idioms are defined as words with a figurative meaning not deducible from their individual components. |
| Approach: | They compare idiom translation as compared to conventional news translation in two languages . they compare MT and SLT systems with MT, Large Language Models and cascaded alternatives . |
| Outcome: | The proposed systems show better handling of idioms than standard news translation systems. |
Can Small Vision–Language Models Perform Sign Language Translation? (2026.findings-acl)
Copied to clipboard
| Challenge: | Vision-Language Models (VLMs) have shown strong generalization across multimodal tasks, but their capacity to handle sign language translation (SLT) remains unclear. |
| Approach: | They propose entity- and semantics-aware metrics tailored for SLT to evaluate their performance. |
| Outcome: | The proposed metrics highlight the limitations of general-purpose VLMs to SLT, unlike their applicability in other tasks. |
J-Shuwa: A Large-Scale Web-Collected Japanese Sign Language-Japanese Parallel Corpus (2026.findings-acl)
Copied to clipboard
| Challenge: | Japanese Sign Language (JSL) is a low-resource sign language that has received limited attention in the AI community due to the lack of large-scale, publicly available parallel corpora. |
| Approach: | They propose a large-scale JSL-Japanese parallel corpus constructed from YouTube videos with hard-coded subtitles and closed captions. |
| Outcome: | The proposed model is effective for training models and can be used for future research across a wide range of tasks. |
Selective Contrastive Learning For Gloss Free Sign Language Translation (2026.acl-long)
Copied to clipboard
| Challenge: | Recent SLT systems adopt CLIP-like Vision-Language pretraining, but the random in-batch contrast provides few, batch-dependent negatives. |
| Approach: | They propose a method to train sign video-text similarity over a time period of 3 months . they use a random in-batch contrast strategy to track negative video- text similarity . |
| Outcome: | The proposed system improves sign language translation by focusing on challenging negatives . the results show that the random in-batch contrast provides few negatives and noisy supervision . |