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pro vyhledávání: '"Tyagi, Shubhi"'
Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE). However, existing approaches for cIE suffer from two limitations: (i) they
Externí odkaz:
http://arxiv.org/abs/2404.12788
We introduce ReFinED, an efficient end-to-end entity linking model which uses fine-grained entity types and entity descriptions to perform linking. The model performs mention detection, fine-grained entity typing, and entity disambiguation for all me
Externí odkaz:
http://arxiv.org/abs/2207.04108
Developing Text Normalization (TN) systems for Text-to-Speech (TTS) on new languages is hard. We propose a novel architecture to facilitate it for multiple languages while using data less than 3% of the size of the data used by the state of the art r
Externí odkaz:
http://arxiv.org/abs/2104.07777
Publikováno v:
INTERSPEECH 2020: 4407-4411
Recent advances in Text-to-Speech (TTS) have improved quality and naturalness to near-human capabilities when considering isolated sentences. But something which is still lacking in order to achieve human-like communication is the dynamic variations
Externí odkaz:
http://arxiv.org/abs/1912.00955
Akademický článek
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Publikováno v:
Indian Journal of Otolaryngology & Head & Neck Surgery; Sep2023, Vol. 75 Issue 3, p2621-2625, 5p
