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Frederick Gyasi and Tim Schlippe
French is a strategically and economically important language in the regions where the African language Twi is spoken. However, only a very small proportion of Twi speakers in Ghana speak French. The development of a Twi?French parallel corpus and corres...
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Mikel Penagarikano, Amparo Varona, Germán Bordel and Luis Javier Rodriguez-Fuentes
In this paper, a semisupervised speech data extraction method is presented and applied to create a new dataset designed for the development of fully bilingual Automatic Speech Recognition (ASR) systems for Basque and Spanish. The dataset is drawn from an...
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Deptii Chaudhari and Ambika Vishal Pawar
Misinformation, fake news, and various propaganda techniques are increasingly used in digital media. It becomes challenging to uncover propaganda as it works with the systematic goal of influencing other individuals for the determined ends. While signifi...
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Ayiguli Halike, Aishan Wumaier and Tuergen Yibulayin
Although low-resource relation extraction is vital in knowledge construction and characterization, more research is needed on the generalization of unknown relation types. To fill the gap in the study of low-resource (Uyghur) relation extraction methods,...
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Guangming Ling, Xiaofeng Mu, Chao Wang and Aiping Xu
Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenar...
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Yanna Sang, Yuan Chen and Juwei Zhang
Neural machine translation has achieved good translation results, but needs further improvement in low-resource and domain-specific translation. To this end, the paper proposed to incorporate source language syntactic information into neural machine tran...
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Atnafu Lambebo Tonja, Olga Kolesnikova, Alexander Gelbukh and Grigori Sidorov
Despite the many proposals to solve the neural machine translation (NMT) problem of low-resource languages, it continues to be difficult. The issue becomes even more complicated when few resources cover only a single domain. In this paper, we discuss the...
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Konlakorn Wongpatikaseree, Sattaya Singkul, Narit Hnoohom and Sumeth Yuenyong
Language resources are the main factor in speech-emotion-recognition (SER)-based deep learning models. Thai is a low-resource language that has a smaller data size than high-resource languages such as German. This paper describes the framework of using a...
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Valery Solovyev and Vladimir Ivanov
In a great deal of theoretical and applied cognitive and neurophysiological research, it is essential to have more vocabularies with concreteness/abstractness ratings. Since creating such dictionaries by interviewing informants is labor-intensive, consid...
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Seid Muhie Yimam, Abinew Ali Ayele, Gopalakrishnan Venkatesh, Ibrahim Gashaw and Chris Biemann
The availability of different pre-trained semantic models has enabled the quick development of machine learning components for downstream applications. However, even if texts are abundant for low-resource languages, there are very few semantic models pub...
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