Skip to main content

News about Scitation

In December 2016 Scitation will launch with a new design, enhanced navigation and a much improved user experience.

To ensure a smooth transition, from today, we are temporarily stopping new account registration and single article purchases. If you already have an account you can continue to use the site as normal.

For help or more information please visit our FAQs.

banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1. K. N. Stevens, Acoustic Phonetics (MIT Press, Cambridge, MA, 1998), Chaps. 1–8, pp. 1485.
2. L. Lisker and A. Abramson, “ A cross-language study of voicing in initial stops: Acoustical measurements,” Word 20, 384422 (1964).
3. J. Jiang, M. Chen, and A. Alwan, “ On the perception of voicing in syllable-initial plosives in noise,” J. Acoust. Soc. Am. 119, 10921105 (2006).
4. J. H. Hansen, S. S. Gray, and W. Kim, “ Automatic voice onset time detection for unvoiced stops (/p/,/t/,/k/) with application to accent classification,” Speech Commun. 52, 777789 (2010).
5. V. Stouten and H. Van Hamme, “ Automatic voice onset time estimation from reassignment spectra,” Speech Commun. 51, 11941205 (2009).
6. P. Niyogi and P. Ramesh, “ The voicing feature for stop consonants: Recognition experiments with continuously spoken alphabets,” Speech Commun. 41, 349367 (2003).
7. P. Auzou, C. Ozsancak, R. J. Morris, M. Jan, F. Eustache, and D. Hannequin, “ Voice onset time in aphasia, apraxia of speech and dysarthria: A review,” Clin. Linguist. Phonet. 14, 131150 (2000).
8. M. Sonderegger and J. Keshet, “ Automatic measurement of voice onset time using discriminative structured prediction,” J. Acoust. Soc. Am. 132, 39653979 (2012).
9. C.-Y. Lin and H.-C. Wang, “ Automatic estimation of voice onset time for word-initial stops by applying random forest to onset detection,” J. Acoust. Soc. Am. 130, 514525 (2011).
10. T. V. Ananthapadmanabha, A. P. Prathosh, and A. G. Ramakrishnan, “ Detection of the closure-burst transitions of stops and affricates in continuous speech using the plosion index,” J. Acoust. Soc. Am. 135, 460471 (2014).
11. A. L. Francis, V. Ciocca, and J. M. C. Yu, “ Accuracy and variability of acoustic measures of voicing onset,” J. Acoust. Soc. Am. 113, 10251031 (2003).
12. J. L. Flanagan, Speech Analysis Synthesis and Perception (Springer, New York, 1972).
13. B. Yegnanarayana and S. Gangashetty, “ Epoch-based analysis of speech signals,” Sadhana 36(5 ), 651697 (2011).
14. B. Yegnanarayana and R. Veldhuis, “ Extraction of vocal-tract system characteristics from speech signals,” IEEE Trans. Speech Audio Proc. 6, 313327 (1998).
15. A. P. Prathosh, T. V. Ananthapadmanabha, and A. G. Ramakrishnan, “ Epoch extraction based on integrated linear prediction residual using plosion index,” IEEE Trans. Audio, Speech, Lang. Process. 21(12 ), 24712480 (2013).
16. T. V. Ananthapadmanabha, “ Acoustic factors determining perceived voice quality,” Vocal Fold Physiology—Voice Quality Control, edited by O. Fujimura and M. Hirano (Singular Publishing Group, San Diego, CA, 1995), Chap. 7, pp. 113126.
17. D. G. Childers and A. K. Krishnamurthy, “ A critical review of electroglottography,” CRC Crit. Rev. Bioeng. 12, 131164 (1985).
18. J. S. Garofolo, L. F. Lamel, W. M. Fisher, J. G. Fiscus, D. S. Pallett, and N. L. Dahlgrena, DARPA—TIMIT, Acoustic-phonetic Continuous Speech Corpus, U.S. Department of Commerce, Washington, DC (1993) (NISTIR Publication No. 4930).
19.“CMU corpora,” URL (Last viewed March 20, 2014).

Data & Media loading...


Article metrics loading...



This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd