Open AccessEnglish Phonetic Synthesis Based on DFGA G2P Conversion Algorithm
Author(s) -
HongLin Chen
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1533/3/032031
Subject(s) - grapheme , computer science , generalization , vocabulary , natural language processing , thesaurus , artificial intelligence , algorithm , speech recognition , linguistics , mathematics , engineering , mathematical analysis , philosophy , graphene , chemical engineering
In English phonetic synthesis, it is impossible to create a thesaurus containing all vocabulary as English has an almost unlimited vocabulary. Hence, for English words that are not included in the thesaurus, generating phonetic symbols through the “Grapheme-to-phoneme (G2P)” algorithm is the best solution. For this purpose, a dynamic finite generalization (DFGA) machine learning algorithm for the rules of G2P conversion is proposed in this paper. The dictionary library used for learning has 27,040 words, 90% of which are used for rule learning, and the remaining 10% are used for testing. After ten rounds of cross-validation, the average grapheme conversion accuracy in the learning and test sets is 99.78% and 93.14%, and the average vocabulary conversion accuracy is 99.56% and 73.51%, respectively.