13th Annual Conference of the International Speech Communication Association

Portland, OR, USA
September 9-13, 2012

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

Keigo Kubo, Hiromichi Kawanami, Hiroshi Saruwatari, Kiyohiro Shikano

Graduate School of Information Science, Nara Institute of Science and Technology, Japan

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

Full Paper

Bibliographic reference.  Kubo, Keigo / Kawanami, Hiromichi / Saruwatari, Hiroshi / Shikano, Kiyohiro (2012): "Evaluation of many-to-many alignment algorithm by automatic pronunciation annotation using web text mining", In INTERSPEECH-2012, 2318-2321.