100
Views
6
CrossRef citations to date
0
Altmetric
Articles

A Robust Syllable Centric Pronunciation Model for Tamil Text To Speech Synthesizer

ORCID Icon &

REFERENCES

  • G. Bharadwaja Kumar , K. N. Murthy , and B. B. Chaudhuri , “Statistical analyses of Telugu text corpora,” Int. J. Dravidian Linguist. , Vol. 36, no. 2, pp. 71–99, 2007.
  • A. Bellur , K. B. Narayan , K. Raghava Krishnan , and H. A. Murthy , “Prosody modeling for syllable-based concatenative speech synthesis of Hindi and Tamil,” in Proceedings of National Conference on Communications , IEEE, Bangalore , India , 2011, pp. 1–5.
  • A. Pradhan , S. Aswin Shanmugam , A. Prakash , K. Veezhinathan , and H. Murthy , “A syllable based statistical text to speech system,” in Proceedings of the 21st European Signal Processing Conference (EUSIPCO) , IEEE, Marrakech , Morocco , 2013, pp. 1–5.
  • S. Yuvaraja , V. Keri , S. C. Pammi , K. Prahallad , and A. W. Black , “Building a Tamil voice using HMM segmented labels,” in National Conference on Communication , International Institute of Information Technology, Hyderabad, India, Language Technologies Institute, Carnegie Mellon University, USA, 2010.
  • K. R. Krishnan , S. Aswin Shanmugam , G. R. Anusha Prakash Kasthuri , and H. A. Murthy , “IIT Madras's submission to the blizzard challenge 2014,” in Proceedings of the Blizzard Challenge Workshop , Singapore , 2014.
  • H. A. Patil , T. B. Patel , N. J. Shah , H. B. Sailor , R. Krishnan , G. R. Kasthuri , T. Nagarajan , L. Christina , N. Kumar , V. Raghavendra , et al. , “A syllable-based framework for unit selection synthesis in 13 Indian languages,” in International Conference in Oriental COCOSDA held jointly with 2013 Conference on Asian Spoken Language Research and Evaluation (O-COCOSDA/CASLRE) , IEEE, Gurgaon , India , 2013, pp. 1–8.
  • K. S. Prahallad and A. W. Black , “Unit size in unit selection speech synthesis,” in Proceedings of the Interspeech , Geneva , Switzerland , 2003.
  • L. Jiang , H.-W. Hon , and X. Huang , “Improvements on a trainable letter-to-sound converter,” in Proceedings of the Fifth European Conference on Speech Communication and Technology , Rhodes , Greece , 1997.
  • J. Lee , and G. G. Lee , “A data-driven grapheme-to-phoneme conversion method using dynamic contextual converting rules for Korean TTS systems,” Comput. Speech Lang. , Vol. 23, no. 4, pp. 423–34, 2009.
  • R. I. Damper , Y. Marchand , M. J. Adamson , and K. Gustafson , “Comparative evaluation of letter-to-sound conversion techniques for English text-to-speech synthesis,” in Proceedings of the third ESCA/COCOSDA Workshop (ETRW) on Speech Synthesis , Jenolan Caves House, Blue Mountains, NSW, Australia, 1998, pp. 53–58.
  • S. Hussain , “Letter-to-sound conversion for Urdu Text-To-Speech system,” in Proceedings of the Workshop on Computational Approaches to Arabic Script-Based Languages, Association for Computational Linguistics , Geneva , Switzerland , 2004, pp. 74–9.
  • A. K. Kienappel and R. Kneser , “Designing very compact decision trees for grapheme-to-phoneme transcription,” in Proceedings of the Interspeech, Aalborg, Denmark , 2001, pp. 1911–4.
  • C. Ma , M. A. Randolph , and J. Drish , “A support vector machines-based rejection technique for speech recognition,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Proceedings (ICASSP’01) , IEEE, 2001, Vol. 1, pp. 381–4.
  • J. R. Bellegarda , “Unsupervised, language-independent grapheme-to-phoneme conversion by latent analogy,” Speech Commun. , Vol. 46, no. 2, pp. 140–52, 2005.
  • M. Bisani and H. Ney , “Joint-sequence models for grapheme-to-phoneme conversion,” 2008a, Speech Commun. , Vol. 50, no. 5, pp. 434–51, 2008.
  • S. Jiampojamarn and G. Kondrak. , “Letter-phoneme alignment: An exploration,” in Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics , Uppsala , Sweden , 2010, pp. 780–8.
  • J. R. Novak , N. Minematsu , and K. Hirose , “WFST-based grapheme-to-phoneme conversion: Open source tools for alignment, model-building and decoding,” in Proceedings of the 10th International Workshop on Finite State Methods and Natural Language Processing , Donostia - San Sebastian, Spain , 2012, pp. 45–9.
  • K. Rao , F. Peng , H. Sak , and F. Beaufays , “Grapheme-to-phoneme conversion using long short-term memory recurrent neural networks,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , IEEE, Brisbane, QLD, Australia , 2015, pp. 4225–9.
  • H. Sak , A. Senior , and F. Beaufays , “Long short-term memory based recurrent neural network architectures for large vocabulary speech recognition,” in CoRR, Vol. abs/1402.1128. Available: http://arxiv.org/abs/1402.1128, eprint. 1402.1128, 2014.
  • H. A. Murthy , A. Bellur , V. Viswanath , B. Narayanan , A. Susan , G. Kasthuri , and R. Krishnan , “Building unit selection speech synthesis in Indian languages: An initiative by an Indian consortium,” in Proceedings of the COCOSDA , Kathmandu, Nepal , 2010.
  • A. W. Black , K. Lenzo , and V. Pagel , “Issues in building general letter to sound rules,” in The Third ESCA/COCOSDA Workshop (ETRW) on Speech Synthesis , Enolan Caves House, Blue Mountains, NSW, Australia, November 26–29, 1998.
  • M. A. Kumar , V. Dhanalakshmi , R. U. Rekha , K. P. Soman , and S. Rajendran , “A novel data driven algorithm for Tamil morphological generator,” Int. J. Comput. Appl. , Vol. 6, no. 12, pp. 52–56, 2010.
  • A. G. Ramakrishnan , L. N. Kaushik , and L. Narayanan , “Natural language processing for Tamil TTS,” in Proceedings of the 3rd Language and Technology Conference , Poznan, Poland , pp. 192–6, 2007.
  • A. Parlikar , S. Sitaram , and A. W. Black , “The Festvox Indic frontend for grapheme to phoneme conversion,” in Proceedings of the 3rd Workshop on Indian Language Data: Resources and Evaluation , Portoroz, Slovenia , 2016.
  • K. S. Prahallad , A. Vadapalli , S. Kesiraju , H. A. Murthy , S. Lata , T. Nagarajan , M. Prasanna , H. Patil , A. K. Sao , S. King , et al. , 2014. “The blizzard challenge,” in Proceedings of the Blizzard Challenge Workshop , Singapore , 2014.
  • S. Nair , C. R. Rechitha , and C. Santhosh Kumar , “Rule-based grapheme to phoneme converter for Malayalam,” Int. J. Comput. Linguist. Nat. Lang. Proc. , 2013.
  • A. Baby , N. L. Nishanthi , A. L. Thomas , and H. A. Murthy , “A unified parser for developing Indian language text to speech synthesizers,” in International Conference on Text, Speech, and Dialogue , Springer, Brno , Czech Republic , 2016, pp. 514–21.
  • G. Bharadwaja Kumar and M. J. J. Premkumar , “Issues in developing LVCSR system for Dravidian languages: An exhaustive case study for Tamil,” Int. J. Comput. Appl ., Vol. 70, no. 19, 2013.
  • E. Veera Raghavendra , S. Desai , B. Yegnanarayana , A. W. Black , and K. Prahallad , “Global syllable set for building speech synthesis in Indian languages,” in IEEE Spoken Language Technology workshop , SLT , Goa , India , 2008. pp. 49–52.
  • S. Jiampojamarn , G. Kondrak , and T. Sherif , “Applying many-to-many alignments and hidden Markov models to letter-to-phoneme conversion,” in HLT-NAACL , Vol. 7, Rochester, New York , 2007, pp. 372–9.
  • N. Udhyakumar , C. S. Kumar , R. Srinivasan , and R. Swaminathan , “Decision tree learning for automatic grapheme-to-phoneme conversion for Tamil,” in Proceedings of the 9th Conference Speech and Computer , St. Petersburg , Russia , 2004.
  • A. S. Kurian , B. Narayan , N. Madasamy , A. Bellur , R. Krishnan , G. Kasthuri , M. V. Vinodh , H. A. Murthy , and K. Prahallad , “Indian language screen readers and syllable based festival text-to-speech synthesis system,” in Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies , Association for Computational Linguistics, Edinburgh , Scotland , 2011, pp. 63–72.
  • S. Karpagavalli and E. Chandra , “A hierarchical approach in Tamil phoneme classification using support vector machine,” Indian J. Sci. Technol. , Vol. 8, no. 35, 2015,.
  • K. Karunakaran and V. Jeya , Mozhiyiyal (in Tamil) . Chennai : Kavitha Pathippakam, 1997.
  • M. Pushpa and S. Karpagavalli , “Multi-label classification: Problem transformation methods in Tamil phoneme classification,” Procedia Comput. Sci. , Vol. 115, pp. 572–9, 2017.
  • B. Hixon , E. Schneider , and S. L. Epstein , “Phonemic similarity metrics to compare pronunciation methods,” in Proceedings of the Interspeech , Florence , Italy , 2011, pp. 825–8,
  • B. Babych , “Graphonological levenshtein edit distance: Application for automated cognate identification,” Baltic J. Modern Comput. , Vol. 4, no. 2, pp. 115–28, 2016.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.