Nvidia corporation (20240427990). TEXT NORMALIZATION AND INVERSE TEXT NORMALIZATION FOR MULTI-LINGUAL LANGUAGE MODELS
Contents
TEXT NORMALIZATION AND INVERSE TEXT NORMALIZATION FOR MULTI-LINGUAL LANGUAGE MODELS
Organization Name
Inventor(s)
Enas Abdullah M Albasiri of Brooklyn NY (US)
Oluwatobi Olabiyi of Falls Church VA (US)
Mariana Voronel of New York NY (US)
TEXT NORMALIZATION AND INVERSE TEXT NORMALIZATION FOR MULTI-LINGUAL LANGUAGE MODELS
This abstract first appeared for US patent application 20240427990 titled 'TEXT NORMALIZATION AND INVERSE TEXT NORMALIZATION FOR MULTI-LINGUAL LANGUAGE MODELS
Original Abstract Submitted
systems and methods provide for a machine learning system to tokenize, classify, and generate representations from a provided input to provide a combined output. an input may be received and processed into tokens for classification based on semiotic classes. for a given semiotic class, particular rule-based algorithms may be selected to generate a desired output for a selected output language. an input may include an auditory or textual input, which may be in a different language from the selected output language, where the particular rule-based algorithms may include morphological rules for particular semiotic classes. different rule-based algorithms may be modularly generated for particular languages and semiotic classes to build a library of models for processing different inputs.
