Evaluation of Many-to-Many Alignment Algorithm by Automatic Pronunciation Annotation Using Web Text Mining

摘要

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.