Croatian HMM-based speech synthesis

Journal of Computing and Information Technology

Volumn 14, Issue 4, 2006, Pages 307-313

  Martincic Ipsic, S ^a   Ipsic, I ^a  

^a University of Rijeka   (Croatia)

Author keywords

Context dependent acoustic modelling; Corpus based speech synthesis; Croatian speech corpora; Hidden Markov models

Indexed keywords

MARKOV PROCESSES; SPEECH; SPEECH RECOGNITION; SPEECH SYNTHESIS;

ACOUSTIC MODELLING; CONTEXT DEPENDENT; CORPUS-BASED SPEECH SYNTHESIS; HMM-BASED SPEECH SYNTHESIS; SOURCE-FILTER MODELS; SPEECH CORPORA; SPEECH SYNTHESIS SYSTEM; SPEECH UTTERANCE;

HIDDEN MARKOV MODELS;

EID: 34547505602     PISSN: 13301136     EISSN: 18463908     Source Type: Journal    
DOI: 10.2498/cit.2006.04.06     Document Type: Article

References (19)

1. A. ACERO, Formant Analysis and Synthesis Using HiddenMarkov Models. EUROSPEECH, Budapest, Hungary, p.p. 1047-1050. 1999
2. J. BAKRAN, N. LAZIC, Fonetski problemi difonske sinteze hrvatskog govora. Govor XV, 1998., Vol. 2, pp. 103-116
3. M. J. BARROS, ET AL., HMM-based European Portuguese TTS System, INTERSPEECH '05, Lisbon, Portugal, 205., pp. 2581-2584
4. N. CAMPBELL, AND A. BLACK, Prosody and the selection of source units for concatenative synthesis, Progress in Speech Synthesis, ed
5. D. H. KLATT, Review of Text to Speech Conversion for English, Journal of the Acoustic Society of America, 1987., Vol. 82, pp. 737-793
6. R. E. DONOVAN, P. C. WOODLAND, A hidden Markov-model-based trainable speech synthesizer. Computer Speech and Language, 1999., Vol. 00, pp. 1-19
7. T. FUKADA, K. TOKUDA, T. KOBAYASHI, AND S. IMAI, An adaptive algorithm for melcepstral analysis of speech, Proc. of ICASSP, 1992., Vol. 1, pp. 137-140
8. K. TOKUDA, ET AL., An algorithm for speech parameter generation from continuous mixtureHMMs with dynamic features. EUROSPEECH 95, 1995., 1: pp. 757-760
9. S. MARTINCIC-IPSIC, I. IPSIC, Recognition of Croatian Broadcast Speech. L. Budin (ed.), S. Ribari ć (ed.).XXVII. MIPRO 2004, Opatija, 2004., Vol. CTS + CIS, pp. 111-114
10. S. MARTINCIC-IPSIC, I. IPSIC, Croatian Telephone Speech Recognition. L. Budin (ed.), S. Ribaric (ed.). To appear in XXIX. MIPRO 2006, Opatija, 2006., Vol. CTS + CIS
11. L. R. RABINER, A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE, 1989., Vol. 77, No. 2, pp. 257-286
12. K. TOKUDA, ET AL., Multi-Space Probability Distribution HMM. IEICE Trans. Inf. & System., Vol. E85-D, No. 3, March, 2003
13. K. TOKUDA, H. ZEN, A. BLACK, An HMM-Based Speech Synthesis System Applied to English. IEEE TTS Workshop 2002. Santa Monica. California, USA. 2002
14. K. TOKUDA, ET AL., Speech Parameter Generation Algorithm for HMM-Based Speech Synthesis. HMM, Proc. ICASSP., 2000., Vol. 3. pp. 1314-1318
15. S. YOUNG, ET AL., The HTK Book (for HTK Version 3.2). Cambridge University Engineering Department, Cambridge, Great Britain. 2002
16. B. VESNICER, F.MIHELIC, Sinteza slovenskega govora z uporabo prikritih Markovovih modelov. Elektrotehniski vestnik, 2004., Vol. 71, No. 4, pp. 223-228
17. Department of Computer Science, Nagoya Institute of Technology, Speech Signal Processing Toolkit, SPTK 3.0. Reference manual, http://ktlab. ics.nitech.ac.jp/~tokuda/SPTK/, Japan, December, 2003. [09.2005.]
18. Department of Computer Science, Nagoya Institute of Technology, HTS HMM Based Speech Synthesis System 1.0. http://hts.ics.nitech.ac.jp/, Japan, 2004. [09.2005.]
19. van Santen, J. Sproat, R., Olive, J., Hirsberg J., Springer, New York, 1997., pp. 663-666