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Traditionally, many text-mining tasks treat individual word-tokens as the finest meaningful semantic granularity. However, in many languages and specialized corpora, words are composed by concatenating semantically meaningful subword structures. Word-level analysis cannot leverage the semantic information present in such subword structures. With regard to word embedding techniques, this leads to not only poor embeddings for infrequent words in long-tailed text corpora but also weak capabilities for handling out-of-vocabulary words. In this paper we propose MorphMine for unsupervised morpheme segmentation. MorphMine applies a parsimony criterion to hierarchically segment words into the fewest number of morphemes at each level of the hierarchy. This leads to longer shared morphemes at each level of segmentation. Experiments show that MorphMine segments words in a variety of languages into human-verified morphemes. Additionally, we experimentally demonstrate that utilizing MorphMine morphemes to enrich word embeddings consistently improves embedding quality on a variety of of embedding evaluations and a downstream language modeling task.
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How to encode arbitrarily complex morphology in word embeddings, no corpus needed
In this paper, we present a straightforward technique for constructing interpretable word embeddings from morphologically analyzed examples (such as interlinear glosses) for all of the world’s languages. Currently, fewer than 300-400 languages out of approximately 7000 have have more than a trivial amount of digitized texts; of those, between 100-200 languages (most in the Indo-European language family) have enough text data for BERT embeddings of reasonable quality to be trained. The word embeddings in this paper are explicitly designed to be both linguistically interpretable and fully capable of handling the broad variety found in the world’s diverse set of 7000 languages, regardless of corpus size or morphological characteristics. We demonstrate the applicability of our representation through examples drawn from a typologically diverse set of languages whose morphology includes prefixes, suffixes, infixes, circumfixes, templatic morphemes, derivational morphemes, inflectional morphemes, and reduplication.
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- PAR ID:
- 10505683
- Editor(s):
- Serikov, Oleg; Voloshina, Ekaterina; Postnikova, Anna; Klyachko, Elena; Neminova, Ekaterina; Vylomova, Ekaterina; Shavrina, Tatiana; Le Ferrand, Eric; Malykh, Valentin; Tyers, Francis; Arkhangelskiy, Timofey; Mikhailov, Vladislav; Fenogenova, Alena
- Publisher / Repository:
- International Conference on Computational Linguistics
- Date Published:
- Journal Name:
- Proceedings of the First Workshop on NLP Applications to Field Linguistics
- Page Range / eLocation ID:
- 64-76
- Format(s):
- Medium: X Other: pdf
- Location:
- Gyeongju, South Kore
- Sponsoring Org:
- National Science Foundation
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