The need for robust pronunciation annotation over out-of-vocabulary (OOV) words has been increasing with the development of an application that deals with proper nouns and brand-new words, such as Voice Search. In robust pronunciation annotation over OOV words, the alignment between graphemes and phonemes is vital data. For a many-to-many alignment algorithm between graphemes and phonemes, we describe its problems and methods to overcome them. An evaluation experiment of a many-to-many alignment by automatic pronunciation annotation using Web text mining is also performed. That experimental result shows that the proposed many-to-many alignment produces an alignment that has the high generalization ability for OOV words while avoiding degradation of the accuracy of the pronunciation annotation compared with the conventional approach.
Index Terms: string alignment, out-of-vocabulary word, pronunciation annotation
Cite as: Kubo, K., Kawanami, H., Saruwatari, H., Shikano, K. (2012) Evaluation of many-to-many alignment algorithm by automatic pronunciation annotation using web text mining. Proc. Interspeech 2012, 2318-2321, doi: 10.21437/Interspeech.2012-608
@inproceedings{kubo12b_interspeech,
author={Keigo Kubo and Hiromichi Kawanami and Hiroshi Saruwatari and Kiyohiro Shikano},
title={{Evaluation of many-to-many alignment algorithm by automatic pronunciation annotation using web text mining}},
year=2012,
booktitle={Proc. Interspeech 2012},
pages={2318--2321},
doi={10.21437/Interspeech.2012-608}
}