Inducing Multilingual Text Analysis Tools Using Bidirectional Recurrent Neural Networks
This work focuses on the rapid development of linguistic annotation tools for resource-poor languages. We experiment several cross-lingual annotation projection methods using Recurrent Neural Networks (RNN) models. The distinctive feature of our approach is that our multilingual word representation requires only a parallel corpus between the source and target language. More precisely, our method has the following characteristics: (a) it does not use word alignment information, (b) it does not assume any knowledge about foreign languages, which makes it applicable to a wide range of resource-poor languages, (c) it provides truly multilingual taggers. We investigate both uni- and bi-directional RNN models and propose a method to include external information (for instance low level information from POS) in the RNN to train higher level taggers (for instance, super sense taggers). We demonstrate the validity and genericity of our model by using parallel corpora (obtained by manual or automatic translation). Our experiments are conducted to induce cross-lingual POS and super sense taggers.
Code (0)
등록된 구현이 없습니다.
Tasks
POSTranslationWord AlignmentSimilar Papers 제목 키워드 기반
It's not Greek to mBERT: Inducing Word-Level Translations from Multilingual BERT
Recent works have demonstrated that multilingual BERT (mBERT) learns rich cross-lingual representations, that allow for transfer across languages. We study the word-level translation information embedded in mBERT and pre…
TranslationIt’s not Greek to mBERT: Inducing Word-Level Translations from Multilingual BERT
Recent works have demonstrated that multilingual BERT (mBERT) learns rich cross-lingual representations, that allow for transfer across languages. We study the word-level translation information embedded in mBERT and pre…
TranslationMultilingual Text-to-Image Person Retrieval via Bidirectional Relation Reasoning and Aligning
Text-to-image person retrieval (TIPR) aims to identify the target person using textual descriptions, facing challenge in modality heterogeneity. Prior works have attempted to address it by developing cross-modal global o…
Person RetrievalAdaptation of Deep Bidirectional Multilingual Transformers for Russian Language
The paper introduces methods of adaptation of multilingual masked language models for a specific language. Pre-trained bidirectional language models show state-of-the-art performance on a wide range of tasks including re…
Natural Language InferenceParaphrase IdentificationQuestion AnsweringReading Comprehension+2Amrita@LT-EDI-EACL2021: Hope Speech Detection on Multilingual Text
Analysis and deciphering code-mixed data is imperative in academia and industry, in a multilingual country like India, in order to solve problems apropos Natural Language Processing. This paper proposes a bidirectional l…
Hope Speech Detection