Automatic recognition of gemination in Japanese motivated by perceptual experiments
-
- Short Greg
- Graduate School of Information Science and Technology, University of Tokyo
-
- Hirose Keikichi
- Graduate School of Information Science and Technology, University of Tokyo
-
- Minematsu Nobuaki
- Graduate School of Engineering, University of Tokyo
Search this article
Abstract
For Japanese speech processing, being able to automatically recognize between geminate and singleton consonants can have many benefits. In standard recognition methods, hidden Markov Models (HMMs) are used. However, HMMs are not good at differentiating between items that are distinguished primarily by temporal differences rather than spectral differences. Also, gemination depends on the length of the sounds surrounding the consonant. Because of this, we propose the construction of a method that automatically distinguishes geminates from singletons and takes these factors into account. In order to do this, it is necessary to determine which surrounding sounds are cues and what the mechanism of human recognition is. For this, we conduct perceptual experiments to examine the relationship between surrounding sounds and primary cues. Then, using these results, we design a method that can automatically recognize gemination. We test this method on two datasets including a speaking rate database. The results attained well-outperform the HMM-based method and overall outperform the case when only the primary cue is used for recognition as well as show more robustness against speaking rate.
Journal
-
- Acoustical Science and Technology
-
Acoustical Science and Technology 35 (2), 73-85, 2014
ACOUSTICAL SOCIETY OF JAPAN
- Tweet
Details 詳細情報について
-
- CRID
- 1390282680066253696
-
- NII Article ID
- 130003390797
- 40019998817
-
- NII Book ID
- AA11501808
-
- ISSN
- 13475177
- 03694232
- 13463969
-
- NDL BIB ID
- 025307242
-
- Text Lang
- en
-
- Data Source
-
- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed