Nearest Neighbour-Based Indonesian G2P Conversion
Abstract: Grapheme-to-phoneme
conversion (G2P), also known as letter-to-sound conversion, is an important module
in both speech synthesis and speech recognition. The methods of G2P give
varying accuracies for different languages although they are designed to be
language independent. This paper discusses a new model based on the pseudo
nearest neighbour rule (PNNR) for Indonesian G2P. In this model, a partial
orthogonal binary code for graphemes, contextual weighting, and neighbourhood weighting
are introduced. Testing to 9,604 unseen words shows that the model parameters
are easy to be tuned to reach high accuracy. Testing to 123 sentences
containing homographs shows that the model could disambiguate homographs if it
uses a long graphemic context.Compared to an information gain tree, PNNR gives
a slightly higher phoneme error rate, but it could disambiguate homographs.
Keywords: grapheme-to-phoneme
conversion, Indonesian language, pseudo nearest neighbour rule, partial
orthogonal binary code, contextual weighting
Author: Suyanto, Agus Harjoko
Journal Code: jptkomputergg140057
