Automatically Tailoring Unsupervised Morphological Segmentation to the Language
Morphological segmentation is beneficial for several natural language processing tasks dealing with large vocabularies. Unsupervised methods for morphological segmentation are essential for handling a diverse set of languages, including low-resource languages. Eskander et al. (2016) introduced a Language Independent Morphological Segmenter (LIMS) using Adaptor Grammars (AG) based on the best-on-average performing AG configuration. However, while LIMS worked best on average and outperforms other state-of-the-art unsupervised morphological segmentation approaches, it did not provide the optimal AG configuration for five out of the six languages. We propose two language-independent classifiers that enable the selection of the optimal or nearly-optimal configuration for the morphological segmentation of unseen languages.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationSegmentationSpeech RecognitionSimilar Papers 제목 키워드 기반
BPE vs. Morphological Segmentation: A Case Study on Machine Translation of Four Polysynthetic Languages
Morphologically-rich polysynthetic languages present a challenge for NLP systems due to data sparsity, and a common strategy to handle this issue is to apply subword segmentation. We investigate a wide variety of supervi…
Machine TranslationSegmentationTranslationBuilding Morphological Chains for Agglutinative Languages
In this paper, we build morphological chains for agglutinative languages by using a log-linear model for the morphological segmentation task. The model is based on the unsupervised morphological segmentation system calle…
SegmentationMorphAGram, Evaluation and Framework for Unsupervised Morphological Segmentation
Computational morphological segmentation has been an active research topic for decades as it is beneficial for many natural language processing tasks. With the high cost of manually labeling data for morphology and the i…
SegmentationExtending the Use of Adaptor Grammars for Unsupervised Morphological Segmentation of Unseen Languages
We investigate using Adaptor Grammars for unsupervised morphological segmentation. Using six development languages, we investigate in detail different grammars, the use of morphological knowledge from outside sources, an…
Towards a First Automatic Unsupervised Morphological Segmentation for Inuinnaqtun
Low-resource polysynthetic languages pose many challenges in NLP tasks, such as morphological analysis and Machine Translation, due to available resources and tools, and the morphologically complex languages. This resear…
Machine TranslationMorphological AnalysisTranslation