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Dynamic Construction of Telugu Speech Corpus for Voice Enabled Text Editor
Kota VN Sunitha, A.Sharada
Pages - 83 - 95     |    Revised - 15-11-2012     |    Published - 31-12-2012
Volume - 3   Issue - 4    |    Publication Date - December 2012  Table of Contents
Speech Corpus, Suggestion List, Text Editor, Signal Comparator, Incremental Growth
In recent decades speech interactive systems have gained increasing importance. Performance of an ASR system mainly depends on the availability of large corpus of speech. The conventional method of building a large vocabulary speech recognizer for any language uses a top-down approach to speech. This approach requires large speech corpus with sentence or phoneme level transcription of the speech utterances. The transcriptions must also include different speech order so that the recognizer can build models for all the sounds present. But, for Telugu language, because of its complex nature, a very large, well annotated speech database is very difficult to build. It is very difficult, if not impossible, to cover all the words of any Indian language, where each word may have thousands and millions of word forms. A significant part of grammar that is handled by syntax in English (and other similar languages) is handled within morphology in Telugu. Phrases including several words (that is, tokens) in English would be mapped on to a single word in Telugu.Telugu language is phonetic in nature in addition to rich in morphology. That is why the speech technology developed for English cannot be applied to Telugu language. This paper highlights the work carried out in an attempt to build a voice enabled text editor with capability of automatic term suggestion. Main claim of the paper is the recognition enhancement process developed by us for suitability of highly inflecting, rich morphological languages. This method results in increased speech recognition accuracy with very much reduction in corpus size. It also adapts Telugu words to the database dynamically, resulting in growth of the corpus.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
Agrawal S. S., “Recent Developments in Speech Corpora in Indian Languages: Country Report of India”, O-COCOSDA 2010, Kathmandu, Nepal.
Akshar Bharathi, Prakash~Rao K, Rajeev Sangal, and S.M.Bendre, “Basic statistical analysis of corpus and cross coparision among corpora”, Technical Report~4, IIIT, Hyderabad,www.iiit.net/techreports/2002.4.pdf, 2002
Atkins, S., J. Clear and N. Ostler. 1992. "Corpus Design Criteria." Literary and Linguistic Computing . 7(1): 1-16.
“Conversational Telugu”, N.D.K.Institute of Languages, 1992.
“Dravidian Phonological Systems”, University of Washington Press, 1975.
“LANGUAGE IN INDIA Strength for Today and Bright Hope for Tomorrow”, Vol 6, August 2006.
”Issues in Indian languages computing in particular reference to search and retrieval in Telugu Language”, Emerald Group Publishing Ltd.
B.Ramakrishna Reddy, “Localist studies in Telugu Syntax”, Ph.D Thesis, University of Edinburgh, 1976.
Bansal, R.K. 1969.The intelligibility of Indian English. Monograph No. 4, CIEFL, Hyderabad.
Barlow, M. 1996. "Corpora for Theory and Practice." International Journal of Corpus inguistics, 1(1): 1-38.
CampbellWN, Isard S D “Segment durations in a syllable frame”, J. Phonetics: Special issue on speechsynthesis 1991 19: 37–47.
Chalapathy Neti, Nitendra Rajput, Ashish Verma, “A Large Vocabulary Continuous Speech Recognition system for Hindi”, In Proceedings of the National conference on Communications, 2002 , Mumbai, pp. 366-370.
D. J. Ravi and Sudarshan Patilkulkarni, “A NovelApproach to Develop Speech Database for Kannada Text-to-Speech System”, Int. J. on Recent Trends in Engineering & Technology,2011, Vol. 05, No. 01, in ACEEE.
Gopalakrishna~Anumanchipalli et. al., “Development of indian language speech databases for large vocabulary speech recognition systems”, Proceedings of International Conference on Speech and Computer(SPECOM), Patras,Greece, Oct 2005.
J.L.Dawson. ”Suffix removal for word conflation”. In Bulletin of the Association for Literary and Linguistic Computing, volume 2(3), pp. 33-46, Michaelmas,1974.
Jinxi Xu and W. Bruce Croft.”Corpus based stemming using co-occurrence of word variants”.ACM Trans.Inf.Syst., 16(1):61-81,1998.
K Subramanyam, D.Arun Kumar,”Static Dictionary for Pronunciation Modeling”, IJRET,Oct 2012, Volume: 1 Issue: 2 , pp.185 – 189.
K.Nagamma Reddy, “Phonetic, Phonological, morpho-syntactic and semantic functions of segmental duration in spoken Telugu:acoustic evidence”.
K.V.N.Sunitha, A.Sharada, “Telugu Text Corpora Analysis for Creating Speech Database”,IJEIT,ISSN 0975-5292, Dec 2009, Volume 1, No.2.
Khan A N, Gangashetty S V, Yegnanarayana B “Syllabic properties of three Indian languages: Implications for speech recognition and language identification”, In Int. Conf.Natural Language Processing, Mysore, India, pp. 125–134, 2003.
L. Deng, and X. Huang, “Challenges in Adopting Speech Recognition”, Communications of ACM, vol. 47, No. 1,pp69-75, Jan 2004.
L. Lamel and G. Adda, "On Designing Pronunciation Lexicons for Large Vocabulary,Continuous Speech Recognition", Proc. International Conference on SpokenLanguage Processing (ICSLP'96), pp6-9, 1996.
M.A. Anusuya · S.K. Katti, “Front end analysis of speech recognition: a review”, Int J Speech Technol (2011) 14: 99–145.
M.F.Porter. “An algorithm for suffix stripping”.In readings in information retrieval, pages 313-316, San Francisco,CA,USA,1997.Morgan Kaufmann Publishers Inc.
M.S. Salam, Dzulkifli Mohamad and S.H. Salleh, “Improved Statistical Speech Segmentation Using Connectionist Approach”, Journal of Computer Science 5 (4): 275-282, 2009 ISSN 1549-3636
N. Usha Rani and P.N. Girija, “Analyzing and Correction of Errors to Improve the Speech Recognition Accuracy for Telugu Language”, CiiT International Journal of Artificial Intelligent Systems and Machine Learning , Issue : June 2011.
Oppenheim, A. V., & Schafer, R.W. (1975). “Digital signal processing”, Englewood Cliffs:Prentice-Hall.
Paice C and Husk G. “Another Stemmer”. In ACM SIGIR Forum 24(3):566,1990.
Prateek Srivastava, Reena Panda&SankarsanRauta, “A Novel, Robust, Hierarchical, TextIndependent Speaker Recognition Technique”, Signal Processing: An International Journal(SPIJ), Volume (6) : Issue (4) : 2012.
Pukhraj P Shrishrimal, Ratnadeep R Deshmukh and Vishal B Waghmare. “Article: Indian Language Speech Database: A Review”, International Journal of Computer Applications 47(5):17-21, June 2012. Published by Foundation of Computer Science, New York, USA.
R.Krovetz. “Viewing morphology as an inference process”. In Proceedings of Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 191-203, 1993.
S. Lokesh, G. Balakrishnan, “Speech Enhancement using Mel-LPC Cepstrum and Vector Quantization for ASR”, European Journal of Scientific Research ISSN 1450-216X Vol.73 No.2 (2012), pp. 202-209.
Size of Speech Corpora ( As on Dec 2011) , Available at: http://www. ldcil.org/resourcesSpeechCorp. Aspx.
Urmila Shrawankar & Vilas Thakare, “Parameters Optimization for Improving ASR Performance in Adverse Real World Noisy Environmental Conditions”, International Journal of Human Computer Interaction (IJHCI), Volume (3) : Issue (3) : 2012 58.
vishwabharat@tdil, MIT Govt. of India Magazine
Young, S., and G. Bloothooft. eds. 1997.Corpus-Based Methods in Language and Speech Precessing.Vol-II.Dordrecht: Kluwer Academic Publishers.
Dr. Kota VN Sunitha
GNITS - India
Dr. A.Sharada
- India

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