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Showing 1 to 4 of 4 for “"Data-to-text"”.

  1. Context-aware data-to-text generation.

    Data-to-Text Generation (D2T) is the subfield of Artificial Intelligence (AI) and Natural Language Processing (NLP) that aims to build systems capable of summarising nonlinguistic structured data into textual reports. D2T systems extract important insights from domain specific, mostly numerical, …

    rgu Repository record for Context-aware data-to-text generation. (opens in a new tab)

  2. Subword segmental neural language generation for Nguni languages

    Deep learning models for text generation are now able to produce fluent and coherent text in many conversational settings. However, such models require large training datasets and are primarily designed for a limited number of high-resource languages. These advances are not directly applicable to

    cape-town Repository record for Subword segmental neural language generation for Nguni languages (opens in a new tab)

  3. Non-linguistic Notions in Language Modeling: Learning, Retention, and Applications

    … linguistic proficiency in their abilities to write, summarize, and phrase, these model have yet to achieve the same remarkability in their ability to quantitatively reason. This deficiency is specially apparent in smaller models (less than 1 Billion parameters) than can run natively …

    vt Repository record for Non-linguistic Notions in Language Modeling: Learning, Retention, and Applications (opens in a new tab)

  4. Foundations for reusable and maintainable surface realisers for isiXhosa and isiZulu

    … Language Generation (NLG) systems are used to generate text in order to reduce manual effort. Most existing systems are built to support European languages with simple and/or well-documented grammars. IsiZulu and isiXhosa, two of the largest South African languages by first language …

    cape-town Repository record for Foundations for reusable and maintainable surface realisers for isiXhosa and isiZulu (opens in a new tab)