The PF-STAR project intended to contribute to establish future activities in the field of multisensorial and multilingual communication (interface technologies) on firmer bases by providing technological baselines, comparative evaluations, and assessment of prospects of core technologies, which future research and development efforts can build from. To this end, the project addressed three crucial areas: technologies for speech-to-speech translation, the detection and expressions of emotional states, and core speech technologies for children. For each of them, promising technologies/approaches were selected, further developed and aligned towards common baselines. The results were assessed and evaluated with respect to both their performances and future prospects. To maximise the impact, the duration of the project was limited to 24 months, and the workplan was designed to delivered results in two stages: at mid-project term (month 14), and at the end of the project. This permitted to make relevant results available as soon as possible, and in particular on time for them to be used during the preparatory phase of the first call of FP6. The Lehrstuhl fΓΌr Informatik 6 was involved in the comparative evaluation and further development of speech translation technologies. The statistical approach was compared to an interlingua based approach. After the evaluation phase, the two approaches were further developed and aligned towards common baselines. PF-STAR was supported by the European Union.
β° 4 days left to apply!
π 2 PhD positions still open:
π― Human-Centred Evaluation Frameworks for Multilingual Technologies
β¨ Multimedia Personalization with Multimodal Large Language Models
π
Deadline: 15 May 2026
π Full details: https://iecs.unitn.it/education/admission/call-for-application
π @lina_conti and @luisabentivogli are heading to #LREC2026 in Palma! They'll present two papers:
π "Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation"
Paper link:
π€ What Matters in Data for DPO? I asked myself this question a few days ago while trying to understand how to generate a dataset with preferences to run #DPO. This recent #NeurIPS paper answered some of my questions. The findings are simple but crucial for data creation:
π Come and join our group! π
We offer 2 fully funded PhD positions:
π Human-Centred Evaluation Frameworks for Multilingual Technologies (A6)
π€ Multimedia Personalization with Multimodal Large Language Models (A7)
β° Deadline: 15 May 2026
π Details: https://iecs.unitn.it/education/admission/call-for-application