895 citations · 980 across the 29 of their papers we have counts for
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Unlabeled Data for Morphological Generation With Character-Based Sequence-to-Sequence Models
Katharina Kann, Hinrich Schütze
We present a semi-supervised way of training a character-based encoder-decoder recurrent neural network for morphological reinflection, the task of generating one inflected word fo…
One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
Katharina Kann, Ryan Cotterell, Hinrich Schütze
We present a novel cross-lingual transfer method for paradigm completion, the task of mapping a lemma to its inflected forms, using a neural encoder-decoder model, the state of the…
Comparative Study of CNN and RNN for Natural Language Processing
Wenpeng Yin, Katharina Kann, Mo Yu +1
Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main t…
Neural Multi-Source Morphological Reinflection
Katharina Kann, Ryan Cotterell, Hinrich Schütze
We explore the task of multi-source morphological reinflection, which generalizes the standard, single-source version. The input consists of (i) a target tag and (ii) multiple pair…