Automatic voice onset time estimation from reassignment spectra

Speech Communication

Volumn 51, Issue 12, 2009, Pages 1194-1205

  Stouten, Veronique ^a   Van hamme, Hugo ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Estimation; Lattice rescoring; Reassignment spectrum; Speech attributes; Voice Onset Time

Indexed keywords

ACOUSTIC EVENTS; HIGH RESOLUTION; LATTICE RESCORING; PHONE RECOGNITION; REASSIGNMENT SPECTRUM; SOURCES OF VARIABILITY; SPEECH RECOGNITION SYSTEMS; SPEECH SIGNALS; TIME-FREQUENCY REPRESENTATIONS; TIMIT DATABASE; VOICE ONSET TIME; VOICED SOUNDS;

ESTIMATION; TELEPHONE SYSTEMS;

SPEECH RECOGNITION;

EID: 69849097501     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.specom.2009.06.003     Document Type: Article

References (24)

1. Auger F., and Flandrin P. Improving the readability of time-frequency and time-scale representations by the reassignment method. IEEE Trans. SP 43 5 (1995) 1068-1089
2. Beyerlein, P., 1998. Discriminative model combination. In: Proc. ICASSP. Seattle, WA, USA, pp. 481-484.
3. Bilmes J., and Bartels C. Graphical model architectures for speech recognition. IEEE SP Mag. 22 5 (2005) 89-100
4. Borden G.J., and Harris K.S. Speech Science Primer: Physiology, Acoustics, and Perception of Speech. second ed. (1984), Williams & Wilkins, Baltimore, USA
5. Demuynck, K., 2001. Extracting, Modelling and Combining Information in Speech Recognition. Ph.D. Thesis, K.U. Leuven, Belgium.
6. Demuynck, K., Van Compernolle, D., Van Hamme, H., 2006. Robust phone lattice decoding. In: Proc. ICSLP. Pittsburgh, USA, pp. 1622-1625.
7. Garofolo, J., Lamel, L., Fisher, W., Fiscus, J., Pallett, D., Dahlgren, N., Zue, V., 1990. The DARPA TIMIT acoustic-phonetic continuous speech corpus. In: Speech Disc 1-1.1, NTIS Order No. PB91-5050651996.
8. Hainsworth, S., Macleod, M., 2003. Time-Frequency Reassignment: A Review and Analysis. Technical Report CUED/FINFENG/TR.459, Cambridge University Engineering Department.
9. Jiang J., Chen M., and Alwan A. On the perception of voicing in syllable-initial plosives in noise. J. ASA 119 2 (2006) 1092-1105
10. Kazemzadeh, A., Tepperman, J., Silva, J., You, H., Lee, S., Alwan, A., Narayanan, S., 2006. Automatic detection of voice onset time contrasts for use in pronunciation assessment. In: Proc. ICSLP, Pittsburgh, PA, USA.
11. King S., and Taylor P. Detection of phonological features in continuous speech using neural networks. Comput. Speech Lang. 14 (2000) 333-353
12. Lee, C.-H., Clements, M.A., Dusan, S., Fosler-Lussier, E., Johnson, K., Juang, B.-H., Rabiner, L., 2007. An overview on automatic speech attribute transcription (asat). In: Proc. INTERSPEECH, Antwerp, Belgium, pp. 1825-1829.
13. Lefebvre, C., Zwierzynski, D., 1990. The use of discriminant neural networks in the integration of acoustic cues for voicing into a continuous-word recognition system. In: Proc. ICSLP, Kobe, Japan, pp. 1073-1076.
14. McCrea C., and Morris R. The effects of fundamental frequency level on voice onset time in normal adult male speakers. J. Speech Lang. Hear. Res. 48 (2005) 1013-1024
15. Niyogi, P., Ramesh, P., 1998. Incorporating voice onset time to improve letter recognition accuracies. In: Proc. ICASSP, Seattle, WA, USA, pp. 13-16.
16. O'Brien S. Spectral features of plosives in connected-speech signals. Internat. J. Man-Machine Studies 38 (1993) 97-127
17. Plante F., Meyer G., and Ainsworth W. Improvement of speech spectrogram accuracy by the method of reassignment. IEEE Trans. SAP 6 3 (1998) 282-286
18. Ramesh, P., Niyogi, P., 1998. The voicing feature for stop consonants: acoustic phonetic analyses and automatic speech recognition experiments. In: Proc. ICSLP, Sydney, Australia.
19. Seppi, D., Falavigna, D., Stemmer, G., Gretter, R., 2007. Word duration modeling for word graph rescoring in lvcsr. In: Proc. INTERSPEECH. Antwerp, Belgium, pp. 1805-1808.
20. Sonmez, K., Plauche, M., Shriberg, E., Franco, H., 2000. Consonant discrimination in elicited and spontaneous speech: a case for signal-adaptive front ends in ASR. In: Proc. ICSLP, Beijing, China.
21. Stouten, F., Martens, J.-P., 2006. Speech recognition with phonological features: some issues to attend. In: Proc. ICSLP, Pittsburgh, PA, USA, pp. 357-360.
22. Whiteside S., Henry L., and Dobbin R. Sex differences in voice onset time: a developmental study of phonetic context effects in british english. J. ASA 116 2 (2004) 1179-1183
23. Witten I., and Bell T. The zero-frequency problem: estimating the probabilities of novel events in adaptive text compression. IEEE Trans. IT 37 4 (1991) 1085-1094
24. Xiao J., and Flandrin P. Multitaper time-frequency reassignment for nonstationary spectrum estimation and chirp enhancement. IEEE Trans. SP 55 6 (2007) 2851-2860