Neural Morphological Segmentation

Neural Morphological Segmentation is a morphological segmentation approach that employs neural network architectures to automatically learn and predict the internal structure of words by identifying their constituent morphemes in an end-to-end differentiable framework.

23

Publications

1.5K

Citations

77

Authors

34

Institutions

Publications per year

2017–2026

9

Authors

77

  1. AT
    Antonio Toral

    Dublin City University, Ireland

    2 publications · 43 citations

    2

    h-index

  2. RC
    Ryan Cotterell

    Johns Hopkins University, United States

    2 publications · 82 citations

    2

    h-index

  3. HS
    Hinrich Schütze

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 82 citations

    2

    h-index

  4. MK
    Mikko Kurimo

    Aalto University, Finland

    2 publications · 24 citations

    2

    h-index

  5. AL
    Andrew Lumsden

    Guy's Hospital, United Kingdom

    2 publications · 209 citations

    2

    h-index

1–5 of 77

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 44 citations

    3

    h-index

  2. Circuits Systems and Signal Processing

    CSSP · 1 publications · 106 citations

    1

    h-index

  3. Development

    1 publications · 183 citations

    1

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  4. Language and Cognitive Processes

    1 publications · 483 citations

    1

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  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 42 citations

    1

    h-index

1–5