Deadline extended to 6th August AoE! :)

| 27 October: World Day for Audiovisual Heritage 2025 🎬 | Today we celebrate the sounds and images that tell humanity’s story and the professionals who ensure those stories transcend language and culture #WorldDayForAudiovisualHeritage #AudiovisualTranslation #Accessibility

💡 I'm happy to share our new article on how language & communication barriers impact mental healthcare for migrants across Europe — based on survey responses from over 600 health & social care professionals in 9 countries https://t.co/Tlj0dPKwKW #1nt #health #mentalhealth

Organizers are happy to help with any questions. 🙂 Website with all details and contacts:

📐Task 3: Quality-informed segment-level error correction Automatically post-edit machine-translated text using quality annotations to generate minimal and accurate corrections. Description: https://t.co/844QeBTI9A Submission platform:

📐Task 2: Span-level error detection Identify and locate translation errors within each segment (start/end indices) and classify their severity. Description: https://t.co/baKvWUuPGq Submission platform:

📐Task 1: Segment-level quality score prediction Predict a quality score for each source–target segment pair, using document-level context and either ESA or MQM annotations. Description: https://t.co/M9oEULegNk Submission platform:

The 2025 MT Evaluation shared task brings together the strengths of the previous Metrics and Quality Estimation tasks under a single, unified evaluation framework. The following tasks are now open (deadline July 31st but participation has never been easier 🙂)

Good luck to all participants! We are incredibly excited to see the innovative solutions you've developed. For full details, baselines, and data formats, visit the official task page. See you in Suzhou! #WMT25 #SharedTask #ComputationalLinguistics #nlproc

🔗 Get the Data & Submit: 📥 Download the Test Set: https://t.co/wmoZPRL8JB (Link is in the "TEST DATA" section) 🏆 Submit on Codabench:

📊 Evaluation: Systems will be ranked on two key metrics: 1️⃣ DeltaCOMET: Primary metric measuring the raw quality improvement over the original MT. 2️⃣ Gain-to-Edit Ratio: DeltaCOMET divided by TER, rewarding systems that are not just effective, but also efficient. #MTeval

🌍 Language Pairs: We're running the task for 6 diverse language pairs, all translating from English: 🇬🇧 EN → 🇨🇳 Chinese (ZH) 🇬🇧 EN → 🇨🇿 Czech (CS) 🇬🇧 EN → 🇮🇸 Icelandic (IS) 🇬🇧 EN → 🇯🇵 Japanese (JA) 🇬🇧 EN → 🇷🇺 Russian (RU) 🇬🇧 EN → 🇺🇦 Ukrainian (UK)

🎯 The Goal: Given a source text, a machine translation, and quality estimation annotations (scores & error spans), the task is to generate a corrected translation. The challenge? Maximum quality improvement while making the fewest possible edits #nlproc #QualityEstimation #APE

Webpage: https://t.co/wmoZPRL8JB Codabench:

📢 Test Set RELEASED! 🚀 The test set for the #WMT25 Shared Task on QE-informed Segment-level Error Correction is now LIVE! It's time to put your MT error correction / APE methods to the test. Let's see how well they can correct machine translation! #NLProc #MT #WMT2025

https://t.co/B9O8bAhk4u

Machine Translation is my first and final love. Every single work I do has some flavor of Machine Translation to it. Machine Translation is the best test bed for any sequence to sequence neural architecture. So it's best you read the book on NMT by the OG MT teacher Prof Philipp

📢 Presenting IndicSeamless: A Speech Translation Model for Indian Languages 🎙️🌍 IndicSeamless is a speech translation model fine-tuned from SeamlessM4Tv2-large on 13 Indian languages. Trained on a curated subset of BhasaAnuvaad, the largest open-source Speech Translation

Prof. Pushpak Bhattacharyya, in conversation with @EconomicTimes, advocates for trinity models—smaller, cost-effective AI models tailored to India’s diverse languages, domains, and tasks. Link: https://t.co/9TxsCiI9nH #CFILT #NLP #AI #LLM