Morphological Segmentation to Improve Crosslingual Word Embeddings for Low Resource Languages

2020 ◽  
Vol 19 (5) ◽  
pp. 1-15
Author(s):  
Santwana Chimalamarri ◽  
Dinkar Sitaram ◽  
Ashritha Jain
Keyword(s):  
Word Embeddings ◽  
Low Resource ◽  
Morphological Segmentation

scholarly journals Incorporating word embeddings in unsupervised morphological segmentation

2020 ◽  
pp. 1-21
Author(s):  
Ahmet Üstün ◽  
Burcu Can
Keyword(s):  
Semantic Information ◽  
Maximum A Posteriori ◽  
Word Embeddings ◽  
A Posteriori ◽  
Low Resource ◽  
A Posteriori Estimate ◽  
Morphological Segmentation ◽  
Vector Representations ◽  
Turkish Language ◽  
Maximum A Posteriori Estimate

Abstract We investigate the usage of semantic information for morphological segmentation since words that are derived from each other will remain semantically related. We use mathematical models such as maximum likelihood estimate (MLE) and maximum a posteriori estimate (MAP) by incorporating semantic information obtained from dense word vector representations. Our approach does not require any annotated data which make it fully unsupervised and require only a small amount of raw data together with pretrained word embeddings for training purposes. The results show that using dense vector representations helps in morphological segmentation especially for low-resource languages. We present results for Turkish, English, and German. Our semantic MLE model outperforms other unsupervised models for Turkish language. Our proposed models could be also used for any other low-resource language with concatenative morphology.

scholarly journals Anchor-based Bilingual Word Embeddings for Low-Resource Languages

2021 ◽  
Author(s):  
Tobias Eder ◽  
Viktor Hangya ◽  
Alexander Fraser
Keyword(s):  
Word Embeddings ◽  
Low Resource

scholarly journals Unsupervised Morphological Segmentation for Low-Resource Polysynthetic Languages

2019 ◽  
Author(s):  
Ramy Eskander ◽  
Judith Klavans ◽  
Smaranda Muresan
Keyword(s):  
Low Resource ◽  
Morphological Segmentation

scholarly journals Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora

2021 ◽  
Author(s):  
Takashi Wada ◽  
Tomoharu Iwata ◽  
Yuji Matsumoto ◽  
Timothy Baldwin ◽  
Jey Han Lau
Keyword(s):  
Word Embeddings ◽  
Parallel Corpora ◽  
Low Resource ◽  
Cross Lingual

scholarly journals Cross-Lingual Word Embeddings for Low-Resource Language Modeling

2017 ◽  
Author(s):  
Oliver Adams ◽  
Adam Makarucha ◽  
Graham Neubig ◽  
Steven Bird ◽  
Trevor Cohn
Keyword(s):  
Language Modeling ◽  
Word Embeddings ◽  
Low Resource ◽  
Cross Lingual
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