Results 11 to 20 of about 1,389,721 (276)
IEEE Access, 2021 Urdu is still considered a low-resource language despite being ranked as world’s $10^{th}$ most spoken language with nearly 230 million speakers.
Abdul Ghafoor +6 more
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AgglutiFiT: Efficient Low-Resource Agglutinative Language Model Fine-Tuning
IEEE Access, 2020 Text classification tends to be difficult when data are inadequate considering the amount of manually labeled text corpora. For low-resource agglutinative languages including Uyghur, Kazakh, and Kyrgyz (UKK languages), in which words are manufactured via
Zhe Li +3 more
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Voice Activation for Low-Resource Languages [PDF]
Applied Sciences, 2021 Voice activation systems are used to find a pre-defined word or phrase in the audio stream. Industry solutions, such as “OK, Google” for Android devices, are trained with millions of samples. In this work, we propose and investigate several ways to train a voice activation system when the in-domain data set is small.
Kolesau, Aliaksei, Šešok, Dmitrij
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Endangered Languages are not Low-Resourced [PDF]
, 2021 The term low-resourced has been tossed around in the field of natural language processing to a degree that almost any language that is not English can be called "low-resourced"; sometimes even just for the sake of making a mundane or mediocre paper appear more interesting and insightful.
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Low-Resource Machine Translation Training Curriculum Fit for Low-Resource Languages
, 2023 We conduct an empirical study of neural machine translation (NMT) for truly low-resource languages, and propose a training curriculum fit for cases when both parallel training data and compute resource are lacking, reflecting the reality of most of the world's languages and the researchers working on these languages. Previously, unsupervised NMT, which
Kuwanto, Garry +5 more
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Transformers for Low-Resource Languages: Is Féidir Linn! [PDF]
, 2021 The Transformer model is the state-of-the-art in Machine Translation. However, in general, neural translation models often under perform on language pairs with insufficient training data. As a consequence, relatively few experiments have been carried out using this architecture on low-resource language pairs.
Lankford, Séamus +2 more
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Corpulyzer: A Novel Framework for Building Low Resource Language Corpora
IEEE Access, 2021 The rapid proliferation of artificial intelligence has led to the development of sophisticated cutting-edge systems in natural language processing and computational linguistics domains.
Bilal Tahir, Muhammad Amir Mehmood
doaj +1 more source
Pre-trained transformer-based language models for Sundanese
Journal of Big Data, 2022 The Sundanese language has over 32 million speakers worldwide, but the language has reaped little to no benefits from the recent advances in natural language understanding.
Wilson Wongso +2 more
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Towards Language Service Creation and Customization for Low-Resource Languages
Information, 2020 The most challenging issue with low-resource languages is the difficulty of obtaining enough language resources. In this paper, we propose a language service framework for low-resource languages that enables the automatic creation and customization of ...
Donghui Lin, Yohei Murakami, Toru Ishida
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Data Augmentation for Low-Resource Neural Machine Translation [PDF]
, 2017 The quality of a Neural Machine Translation system depends substantially on the availability of sizable parallel corpora. For low-resource language pairs this is not the case, resulting in poor translation quality. Inspired by work in computer vision, we
Bisazza, Arianna +2 more
core +2 more sources