Browse > Article
http://dx.doi.org/10.7776/ASK.2012.31.6.353

Nasal Place Detection with Acoustic Phonetic Parameters  

Lee, Suk-Myung (연세대학교 전기전자공학과)
Choi, Jeung-Yoon (연세대학교 전기전자공학과)
Kang, Hong-Goo (연세대학교 전기전자공학과)
Abstract
This paper describes acoustic phonetic parameters for detecting nasal place in a knowledge-based speech recognition system. Initial acoustic phonetic parameters are selected by studying nasal production mechanisms which are radiation of the sound through the nasal cavity. Nasals are produced with differing articulatory configuration which can be classified by measuring acoustic phonetic parameters such as band energy ratio, band energy differences, formants and formant differences. These acoustic phonetic parameters were tested in a classification experiment among labial nasal, alveolar nasal and velar nasal. An overall classification rate of 57.5% is obtained using the proposed acoustic phonetic parameters on the TIMIT database.
Keywords
Nasal; Nasal place; Acoustic phonetic parameters; Speech recognition;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. S. Garofalo, L. F. Lamel, W. M. Fisher, J. G. Fiscus, D. S. Pallett, and N. L. Dahlgren, "The DARPA TIMIT acoustic-phonetic continuous speech corpus CDROM," Linguistic Data Consortium, 1993.
2 P. F. Seitz, M. M. McCormick, M. C. Watson, and R. A. Bladon "Relational spectral features for place of articulation in nasal consonants," J. Acoust. Soc. Am., vol. 87, no. 1, pp. 351-358, 1990.   DOI
3 R. De Mori, and G. Flammia "Speaker-independent consonant classification in continuous speech with distinctive features and neural networks," J. Acoust. Soc. Am., vol. 94, no. 6, pp. 3091-3103, 1993.   DOI   ScienceOn
4 K. N. Stevens, "Toward a model for lexical access based on acoustic landmarks and distinctive features," J. Acoust. Soc. Am., vol. 111, no. 4, pp. 1872-1891, 2002.   DOI   ScienceOn
5 J.R. Glass, and V.W. Zue, "Detection of nasalized vowels in American English," in Proc. ICASSP, pp. 1569-1572, 1985.
6 O. Fujimura, "Analysis of Nasal Consonants," J. Acoust. Soc. Am., vol. 34, no. 12, pp. 1865-1875, 1962.   DOI
7 K. N. Stevens, Acoustic Phonetics, MIT, 1998.
8 R.D. Kent, and C. Read, The Acoustic Analysis of Speech, Thomson Learning, 2001.
9 M.Y. Chen, "Nasal Detection Module for a Knowledgebased Speech Recognition System," in Proc. ICSLP, pp. 636-639, 2000.
10 T. Pruthi, and C. Y. Espy-Wilson, "Acoustic parameters for automatic detection of nasal manner," Speech Communication, vol. 43, pp. 225-239, 2004.   DOI   ScienceOn
11 D. A. Reynolds, and R. C. Rose, "Robust textindependent speaker identification using Gaussian mixture speaker models," IEEE Trans. Speech Audio Process., vol. 3, no. 1, pp. 72-83, 1995.   DOI   ScienceOn
12 J. Gustafson and K. Sjolander, "Educational tools for speech technology," in Proc. Fonetik, pp. 176-179, 1998.