Informal Text Breaks G2P Before Pronunciation Starts
TL;DR for operators A grapheme-to-phoneme system can look accurate on ordinary words and deteriorate sharply when users write abbreviations, slang, lengthenings, or phonetic spellings. In UGTPhon, the largest observed difference between canonical and non-canonical inputs is 66.8 phoneme-error-rate points. The paper’s more consequential result is diagnostic. Some informal forms preserve enough pronunciation information to be read almost directly. Others omit information that must first be recovered from context or prior knowledge. The proposed system therefore keeps sentence context, retrieves an exact-match canonical-form hint when available, and for non-canonical inputs explicitly generates the intended standard form before generating phonemes. ...