Morphological Inflection Generation Using Character Sequence to Sequence Learning
Not on the map. Why?
Abstract (arXiv)
Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation. We model the problem of inflection generation as a character sequence to sequence learning problem and present a variant of the neural encoder-decoder model for solving it. Our model is language independent and can be trained in both supervised and semi-supervised settings. We evaluate our system on seven datasets of morphologically rich languages and achieve either better or comparable results to existing state-of-the-art models of inflection generation.
Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2015.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 7; 2022: 1; 2023: 3; 2024: 2; 2025: 0; 2026: 1.
14 papers.
Sort:
- 2021Smoothing and Shrinking the Sparse Seq2Seq Search Spacecited by 11
- 2023CompoundPiece: Evaluating and Improving Decompounding Performance of Language Modelscited by 7
- 2024Frequency matters: Modeling irregular morphological patterns in Spanish with Transformerscited by 5
- 2022Morphological Processing of Low-Resource Languages: Where We Are and What's Nextcited by 4
- 2021Rule-based Morphological Inflection Improves Neural Terminology Translationcited by 3
- 2023An Investigation of Noise in Morphological Inflectioncited by 3
- 2021Searching for Search Errors in Neural Morphological Inflectioncited by 2
- 2021Computational Morphology with Neural Network Approachescited by 2
- 2021Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflectioncited by 2
- 2021Minimal Supervision for Morphological Inflectioncited by 1
- 2021A Three Step Training Approach with Data Augmentation for Morphological Inflectioncited by 1
- 2026When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphologycited by 1
2 more
- 2023A big data approach towards sarcasm detection in Russiancited by 0
- 2024OOVs in the Spotlight: How to Inflect them?cited by 0
- 2026When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphology19 May 2026
- 2024Frequency matters: Modeling irregular morphological patterns in Spanish with Transformers28 Oct 2024
- 2024OOVs in the Spotlight: How to Inflect them?13 Apr 2024
- 2023A big data approach towards sarcasm detection in Russian1 Jun 2023
- 2023An Investigation of Noise in Morphological Inflection26 May 2023
- 2023CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models23 May 2023
- 2022Morphological Processing of Low-Resource Languages: Where We Are and What's Next16 Mar 2022
- 2021A Three Step Training Approach with Data Augmentation for Morphological Inflection14 Sep 2021
- 2021Rule-based Morphological Inflection Improves Neural Terminology Translation10 Sep 2021
- 2021Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflection9 Aug 2021
- 2021Computational Morphology with Neural Network Approaches19 May 2021
- 2021Minimal Supervision for Morphological Inflection17 Apr 2021
2 more
- 2021Smoothing and Shrinking the Sparse Seq2Seq Search Space18 Mar 2021
- 2021Searching for Search Errors in Neural Morphological Inflection16 Feb 2021
- 2021Smoothing and Shrinking the Sparse Seq2Seq Search Spacecited by 11
- 2023CompoundPiece: Evaluating and Improving Decompounding Performance of Language Modelscited by 7
- 2024Frequency matters: Modeling irregular morphological patterns in Spanish with Transformerscited by 5
- 2022Morphological Processing of Low-Resource Languages: Where We Are and What's Nextcited by 4
- 2021Rule-based Morphological Inflection Improves Neural Terminology Translationcited by 3
- 2023An Investigation of Noise in Morphological Inflectioncited by 3
- 2021Searching for Search Errors in Neural Morphological Inflectioncited by 2
- 2021Computational Morphology with Neural Network Approachescited by 2
- 2021Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflectioncited by 2
- 2021Minimal Supervision for Morphological Inflectioncited by 1
- 2021A Three Step Training Approach with Data Augmentation for Morphological Inflectioncited by 1
- 2026When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphologycited by 1
12 most cited of 14 All 14 (JSON)
- 2026When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphology19 May 2026
- 2024Frequency matters: Modeling irregular morphological patterns in Spanish with Transformers28 Oct 2024
- 2024OOVs in the Spotlight: How to Inflect them?13 Apr 2024
- 2023A big data approach towards sarcasm detection in Russian1 Jun 2023
- 2023An Investigation of Noise in Morphological Inflection26 May 2023
- 2023CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models23 May 2023
- 2022Morphological Processing of Low-Resource Languages: Where We Are and What's Next16 Mar 2022
- 2021A Three Step Training Approach with Data Augmentation for Morphological Inflection14 Sep 2021
- 2021Rule-based Morphological Inflection Improves Neural Terminology Translation10 Sep 2021
- 2021Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflection9 Aug 2021
- 2021Computational Morphology with Neural Network Approaches19 May 2021
- 2021Minimal Supervision for Morphological Inflection17 Apr 2021
12 newest of 14 All 14 (JSON)