There are two interleaved high-level goals for the EXCITEMENT project. The first is to set up, for the first time, a generic architecture and a comprehensive implementation for a multilingual textual inference platform and to make it available to the scientific and technological communities. The second goal of the project is to develop a new generation of inference-based industrial text exploration applications for customer interactions, which enables businesses to better analyze and make sense of their diverse and often unpredicted client content. These goals were be achieved for three languages, i.e. English, German and Italian, and for three customer interaction channels, i.e. speech (transcriptions), email and social media.
New benchmark evaluates π #AI detection tools across languages, π finding performance gaps π in low-resource languages and challenges β οΈ with distinguishing AI-translated and hybrid humanβAI text.
@jasonslucas1 @adaku_uchendu @penn_state @Visa
π Call for Participation: @iwslt Offline Speech Translation 2026
Break language barriers with new languages & real-world scenarios + a brand new source-language agnostic speech translation track π
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Evaluation: Apr 1β15
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#IWSLT2026 #SpeechAI
π Call for Participation: @iwslt Model Compression 2026
Make large multilingual foundation models small β‘ without losing power in ENβDE/ZH speech-to-text translation.
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Evaluation: Apr 1β15
#IWSLT2026 #SpeechAI #Qwen2 #EfficientAI
π Call for Participation: @iwslt Subtitling 2026
Turn speech into ready-to-watch subtitles π¬ across TV, News & YouTube!
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Evaluation: Apr 1β15
#IWSLT2026 #SpeechAI #MultimodalAI