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“Which vocational training program is best for me?” – Design of a recommender system for school students using large language models

Piazza, Alexander; Schacht, Sigurd; Herzog, Michael (2025)

UMAP Adjunct '25: Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization, 425-428.
DOI: 10.1145/3708319.3733809


Peer Reviewed
 

School students need to make decisions about their career paths after graduating. In Germany, students can choose between more than 300 vocational training programs, which can be overwhelming. Frequently, the students hesitate to talk with career counselors. The objective of this research is, therefore, to provide a recommendation system for school students to support their decision-making, which is based on their interests and provides recommendations with explanations based on a LLM. This system was developed with a social robot as the user interface to make it easy to use and appeal to the young target group. Based on user observations, preliminary findings indicate that the system is a valuable and engaging approach to support career counseling activities.


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An approach to optimize inference of the DIART speaker diarization pipeline

Aperdannier, Roman; Schacht, Sigurd; Piazza, Alexander (2024)

Arxiv.
DOI: 10.48550/arXiv.2408.02341


Open Access
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Systematic Evaluation of Online Speaker Diarization Systems Regarding their Latency

Aperdannier, Roman; Schacht, Sigurd; Piazza, Alexander (2024)

Arxiv.
DOI: 10.48550/arXiv.2407.04293


Open Access
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A Review of Common Online Speaker Diarization Methods

Aperdannier, Roman; Schacht, Sigurd; Piazza, Alexander (2024)

Arxiv.
DOI: 10.48550/arXiv.2406.14464


Open Access
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Intro zu ChatGPT & Co - ein Experiment vom AN[ki]T "AI talks to AI"

Schacht, Sigurd; Piazza, Alexander (2023)

KI-Stammtisch des KI-Hub Bayern am Nürnberg DIGITAL FESTIVAL.


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