5 Publikationen

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  • [5]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984549
    Harz, L., Voß, H., & Kopp, S., 2023. FEIN-Z: Autoregressive Behavior Cloning for Speech-Driven Gesture Generation. In E. André, et al., eds. Proceedings of the 25th International Conference on Multimodal Interaction (ICMI '23). New York, NY, USA: ACM, pp. 763–771.
    PUB | DOI
     
  • [4]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2980542
    Voß, H., & Kopp, S., 2023. AQ-GT: A Temporally Aligned and Quantized GRU-Transformer for Co-Speech Gesture Synthesis. In Proceedings of the 25th International Conference on Multimodal Interaction (ICMI 2023). ACM Press.
    PUB | DOI | arXiv
     
  • [3]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2980879
    Voß, H., & Kopp, S., 2023. Augmented Co-Speech Gesture Generation: Including Form and Meaning Features to Guide Learning-Based Gesture Synthesis. In ACM International Conference on Intelligent Virtual Agents (IVA '23). pp. 8.
    PUB | DOI
     
  • [2]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2964824
    Voß, H., 2022. Adaptive Gesture Generation for Goal-directed Interaction Support. In Doctoral Symposium at the 22nd ACM International Conference on Virtual Agents (IVA).
    PUB
     
  • [1]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957396
    Voß, H., Wersing, H., & Kopp, S., 2021. Addressing Data Scarcity in Multimodal User State Recognition by Combining Semi-Supervised and Supervised Learning. In Z. Hammal, ed. Companion Publication of the 2021 International Conference on Multimodal Interaction. New York, NY: Association for Computing Machinery , pp. 317-323.
    PUB | DOI
     

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