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Indian Language Wordnets and their Linkages with Princeton WordNet ...
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Techniques for Jointly Extracting Entities and Relations: A Survey ...
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Knowledge-based Extraction of Cause-Effect Relations from Biomedical Text ...
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How low is too low? A monolingual take on lemmatisation in Indian languages ...
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Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages ...
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M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations ...
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"So You Think You're Funny?": Rating the Humour Quotient in Standup Comedy ...
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Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages ...
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Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study ...
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Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ...
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Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation
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In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2-6 Nov 2020, Lisboa, Portugal. (2020)
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Syntax-informed interactive neural machine translation
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In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Syntax-informed interactive neural machine translation. In: The International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, UK (Online). (2020)
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Extracting N-ary Cross-sentence Relations using Constrained Subsequence Kernel ...
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Related Tasks can Share! A Multi-task Framework for Affective language ...
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Reinforced Multi-task Approach for Multi-hop Question Generation ...
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Utilizing Language Relatedness to improve Machine Translation: A Case Study on Languages of the Indian Subcontinent ...
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Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ...
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Abstract:
Cognates are variants of the same lexical form across different languages; for example "fonema" in Spanish and "phoneme" in English are cognates, both of which mean "a unit of sound". The task of automatic detection of cognates among any two languages can help downstream NLP tasks such as Cross-lingual Information Retrieval, Computational Phylogenetics, and Machine Translation. In this paper, we demonstrate the use of cross-lingual word embeddings for detecting cognates among fourteen Indian Languages. Our approach introduces the use of context from a knowledge graph to generate improved feature representations for cognate detection. We then evaluate the impact of our cognate detection mechanism on neural machine translation (NMT), as a downstream task. We evaluate our methods to detect cognates on a challenging dataset of twelve Indian languages, namely, Sanskrit, Hindi, Assamese, Oriya, Kannada, Gujarati, Tamil, Telugu, Punjabi, Bengali, Marathi, and Malayalam. Additionally, we create evaluation datasets ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://dx.doi.org/10.48448/rjmx-hd61 https://underline.io/lecture/6380-harnessing-cross-lingual-features-to-improve-cognate-detection-for-low-resource-languages
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