CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Theoretical Survey of the Formant Tracking Algorithm

Published on March 2012 by Manisha H. Awatade
journal_cover_thumbnail

2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 2
March 2012
Authors: Manisha H. Awatade
5514c2aa-4918-4447-914d-7053230197af

Manisha H. Awatade . Theoretical Survey of the Formant Tracking Algorithm. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 2 (March 2012), 14-17.

@article{
author = { Manisha H. Awatade },
title = { Theoretical Survey of the Formant Tracking Algorithm },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { March 2012 },
volume = { NCIPET },
number = { 2 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 14-17 },
numpages = 4,
url = { /proceedings/ncipet/number2/5200-1012/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A Manisha H. Awatade
%T Theoretical Survey of the Formant Tracking Algorithm
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 0975-8887
%V NCIPET
%N 2
%P 14-17
%D 2012
%I International Journal of Computer Applications
Abstract

The formant is the important part of the phonetic characters, and reliable formant tracking algorithm is the base to study the phonetics. Based on the development course of the phonetic formant tracking algorithm, the linear prediction coding (LPC) and the model matching method are introduced emphatically, and there own advantages and disadvantages are analyzed, and the model matching method based on the hidden dynamic model will be the development direction of the future formant tracking technology.

References
  1. S.S.McCandless. 1974. An algorithm for automatic formant extraction using linear prediction spectra. IEEE Transactions on Acoustics, Speech, and Signal Processing. No.22(2). p.135-141.
  2. D.J.Broad, F.Clermont. 1989. Formant estimation by linear transformation of the LPC cepstrum. Journal of the Acoustical Society of America. No.86(5). p.2013-2017.
  3. A.M.De Lima Araujo, F.Violaro. (1998). Formant frequency estimation using a mel scale LPC algorithm. Telecommunications Symposium, ITS „98 Proceedings. Vol.1. p.207-212.
  4. D.Talkin. 1987. Speech formant trajectory estimation using dynamic programming with modulated transition costs. Journal Acoustical Society of America. No.82(S1). p.S55.
  5. G..Kopec. 1986. Formant Tracking Using Hidden Markov Models and Vector Quantization. IEEE Transactions on Acoustics, Speech, and Signal processing. No.34(4). p.709-729.
  6. Lee, M.; vanSanten, J.; Mobius, B.; Olive, J.; 2005 Formant tracking using context dependent phonemic information IEEE transaction on speech and audio processing vol.13.p.741-750.
  7. J.K.Baker. 1975. The Dragon System-An overview. IEEE Transactions of Acoustics, Speech, and Signal Processing. No.23(1). p.24-29..
  8. P.Zolfaghari, T.Robinson. 1996. Formant analysis using mixtures of Gaussians. Proc. ICSLP. Vol.2. p.1229-1232.
  9. J.Darch, B.Milner, S.Xu, S.Vaseghi and Y.Qin. 2005. Predicting formant frequencies from MFCC vectors. Proc. ICASSP. Vol.1. p.941-944.
  10. M.Lee, J.vanSanten, B.Mobius, J.Olive. 2005. Formant Tracking Using Context-Dependent Phonemic Information. IEEE Transactions on Speech and Audio Processing. No.13(5). p.741-750.
  11. D.T.Toledano, J.G..Villardebo, L.H.Gomez. 2006. Initialization, training, and context-dependency in HMM-based formant tracking. IEEE Transactions on Acoustics, Speech, and Signal processing. No.14(2). p.511-522.
  12. L.Deng. 1998. A dynamic, feature-based approach to the interface between phonology and phonetics for speech modeling and recognition. Speech Communication. No.24(4). p.299-323.
  13. H.B.Richards, J.S.Bridle. 1999. The HDM: A segmental hidden dynamic model of coarticulation. Proc. ICASSP. Vol.1. p.357-360.
  14. L.Deng, J. Ma. 2000. Spontaneous speech recognition using a statistical coarticulatory model for the vocal-tract-resonance dynamic. Journal of the Acoustical Society of America. No.108(6). p.3036-3048.
  15. L.Deng, L.J.Lee, H.Attias, A.Acero. 2007. Adaptive kalman filtering and smoothing for tracking vocal resonances using a continuous-valued hidden dynamic model. IEEE Transactions on Audio, Speech, and Language processing. No.15(1). p.13-23.
  16. L.Deng, A.Acero, I.Bazzi. 2006. Tracking vocal tract resonances using a quantized nonlinear function embedded in a temporal constraint. IEEE Transactions on Acoustics, Speech, and Language processing. No.14(2). p.425-434.
  17. Yanli.Zheng, M. Hasegawa-Johnson. 2004. Formant tracking by mixture state particle filter. Proc. ICASSP. Vol.1. p.565-568.
Index Terms

Computer Science
Information Sciences

Keywords

Formant Tracking Linear prediction coding Model matching