Jakob Drachmann Havtorn

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Jakob Drachmann Havtorn

  • Richard Petersens Plads, 321, 223

    2800 Kgs. Lyngby

    Denmark

20202021

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  • 4 Article in proceedings

  • Hierarchical VAEs Know What They Don't Know

    Havtorn, J. D., Frellsen, J., Hauberg, S. & Maaløe, L., 2021, Proceedings of the 38th International Conference on Machine Learning. International Machine Learning Society (IMLS), 12 p. (Proceedings of Machine Learning Research, Vol. 139).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    Open Access
    File
    33 Downloads (Pure)

  • On scaling contrastive representations for low-resource speech recognition

    Borgholt, L., Tax, T. M. S., Havtorn, J. D., Maaløe, L. & Igel, C., 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, Vol. 2021-. p. 3885-3889 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    Open Access
    File
    2 Downloads (Pure)

  • Do end-to-end speech recognition models care about context?

    Borgholt, L., Havtorn, J. D., Agic, Ž., Søgaard, A., Maaløe, L. & Igel, C., 2020, Proceedings of the Annual Conference of the International Speech Communication Association. p. 4352-4356 (Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  • MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech

    Havtorn, J. D., Latko, J., Edin, J., Borgholt, L., Maaloe, L., Belgrano, L., Jacobsen, N. F., Sdun, R. & Agic, Z., 2020, Proceedings of 58th Annual Meeting of the Association for Computational Linguistics. p. 2370-2380

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    Open Access
    File
    3 Downloads (Pure)