https://github.com/Aso-UniMelb/neural-fieldwork-guide
공식 코드Can a Neural Model Guide Fieldwork? A Case Study on Morphological Data Collection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Morphological Inflection is the task of generating a target (inflected form) word from a source word (base form), given a morphological attribute, e.g. number, tense, and person etc. It is useful for alleviating data sparsity issues in translating morphologically rich languages. The transformation from a base form to an inflected form usually includes concatenating the base form with a prefix or a suffix and substituting some characters. For example, the inflected form of a Finnish stem eläkeikä (retirement age) is eläkeiittä when the case is abessive and the number is plural.
Source: Tackling Sequence to Sequence Mapping Problems with Neural Networks
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Can a Neural Model Guide Fieldwork? A Case Study on Morphological Data Collection
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation
Falling Through the Gaps: Neural Architectures as Models of Morphological Rule Learning
Rule-based Morphological Inflection Improves Neural Terminology Translation
A Framework for Bidirectional Decoding: Case Study in Morphological Inflection
Morphological Inflection Generation Using Character Sequence to Sequence Learning
Systematic Inequalities in Language Technology Performance across the World's Languages
(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models' Performance
Morphological Inflection Generation with Hard Monotonic Attention
Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding
Exact Hard Monotonic Attention for Character-Level Transduction
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection
Eeny, meeny, miny, moe. How to choose data for morphological inflection
An Extended Sequence Tagging Vocabulary for Grammatical Error Correction
An Extended Sequence Tagging Vocabulary for Grammatical Error Correction
Exact Hard Monotonic Attention for Character-Level Transduction
A Structured Variational Autoencoder for Contextual Morphological Inflection
A Structured Variational Autoencoder for Contextual Morphological Inflection
Systematic Inequalities in Language Technology Performance across the World's Languages
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.