Modified Grapheme Encoding and Phonemic Rule to Improve PNNR-Based Indonesian G2P
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 3
Abstract
A grapheme-to-phoneme conversion (G2P) is very important in both speech recognition and synthesis. The existing Indonesian G2P based on pseudo nearest neighbour rule (PNNR) has two drawbacks: the grapheme encoding does not adapt all Indonesian phonemic rules and the PNNR should select a best phoneme from all possible conversions even though they can be filtered by some phonemic rules. In this paper, a modified partial orthogonal binary grapheme encoding and a phonemic-based rule are proposed to improve the performance of PNNR-based Indonesian G2P. Evaluating on 5-fold cross-validation, contain 40K words to develop the model and 10K words to evaluation each, shows that both proposed concepts reduce the relative phoneme error rate (PER) by 13.07%. A more detail analysis shows the most errors are from grapheme ?e? that can be dynamically converted into either /E/ or /??/ since four prefixes, ’ber’, ’me’, ’per’, and ’ter’, produce many ambiguous conversions with basic words and also from some similar compound words with both different pronunciations for the grapheme ?e?. A stemming procedure can be applied to reduce those errors.
Authors and Affiliations
Suyanto , Sri Hartati, Agus Harjoko
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