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Speech to Text in Marathi Overview

Shrishrimal PP, Deshmukh RR. Design and Development of Spoken Marathi Isolated Words Database for Agriculture Purpose and its Analysis. M. Phil. Computer Science Thesis. 2013 May. Tiwari Speech to Text in Marathi V. MFCC and its applications in speaker recognition. International journal on emerging Speech to Text in Marathi technologies. 2010 Feb;1(1):19-22. Davis S, Mermelstein P. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE transactions on acoustics, speech, and signal processing. 1980 Aug;28(4):357-66. Young S. J., Odell J., Ollason D., Valtchev V., Woodland P., “The HTK Book.Version2.1”,Department Speech to Text in Marathi of Engineering, Cambridge University,UK,1995. “TheSpeech to Text in Marathi NIST Year 2001 Speaker Recognition Evaluation Plan”,The NIST of USA,2001.Available: http://www.nist.gov/speech/tests/spk/2001/doc/2001-spkrec-evalplan-v05.9.pdf. Skowronski MD, Harris JG. Exploiting independent filter bandwidth of human factor cepstral coefficients in automatic speech recognition. The Journal of the Acoustical Society of America. 2004 Sep;116(3):1774-80. Mao X, Chen L, Zhang B. Mandarin speech emotion recognition based on a hybrid of HMM/ANN. international journal of computers. 2007;1(4):321-4. Zhou Y, Sun Y, Yang L, Yan Y. Applying articulatory features to speech emotion recognition. In2009 International Conference on Research Challenges in Computer Science 2009 Dec 28 (pp. 73-76). IEEE. Waghmare VB, Deshmukh RR, Shrishrimal PP, Janvale GB, Ambedkar B. Emotion recognition system from artificial marathi speech using MFCC and LDA techniques. InFifth international conference on advances in communication, network, and computing–CNC 2014. Mao X, Chen L, Zhang B. Mandarin speech emotion recognition based on a hybrid of HMM/ANN. international journal of computers. 2007;1(4):321-4. Drgas S, Dabrowski A. Speaker recognition based on multilevel speech signal analysis on Polish corpus. Multimedia Tools and Applications. 2015 Jun;74:4195-211. Gevaert W, Tsenov G, Mladenov V. Neural networks used for speech recognition. Journal of Automatic control. 2010;20(1):1-7. Vemula Yakub Reddy1, Mangipudi Pava……

Speech to Text in MarathiAbro, S., Sarang Shaikh, Z. A., Khan, S., Mujtaba, G., & Khand, Z. H. (2020). Automatic hate speech detection using machine learning: A comparative study. Machine Learning, 10(6). Alexandrou, A. M., Saarinen, T., Kujala, J., & Salmelin, R. (2016). A multimodal spectral approach to characterize rhythm in natural speech. The Journal of the Acoustical Society of America, 139(1), 215-226. Ali, A., Dehak, N., Cardinal, P., Khurana, S., Yella, S. H., Glass, J., … & Renals, S. (2015). Automatic dialect detection in arabic broadcast speech. arXiv preprint arXiv:1509.06928. Bansod, N. S., Dadhade, S. B., Kawathekar, S. S., & Kale, K. V. (2014, March). Speaker Recognition using Marathi (Varhadi) Language. In 2014 International Conference on Intelligent Computing Applications (pp. 421-425). IEEE. Biadsy, F. (2011). Automatic dialect and accent recognition and its application to speech recognition. Columbia University. Chittaragi, N. B., Limaye, A., Chandana, N. T., Annappa, B., & Koolagudi, S. G. (2019). Automatic text-independent Kannada dialect identification system. In Information Systems Design and Intelligent Applications (pp. 79-87). Springer, Singapore. Elfeky, M. G., Moreno, P., & Soto, V. (2018). Multi-dialectical languages effect on speech recognition: Too much choice can hurt. Procedia Computer Science, 128, 1-8. Etman, A., & Beex, A. L. (2015, November). Language and dialect identification: A survey. In 2015 SAI intelligent systems conference (IntelliSys) (pp. 220-231). IEEE. Gurbuz, S., Gowdy, J. N., & Tufekci, Z. (2000, April). Speech spectrogram-based model adaptation for speaker identification. In Proceedings of the IEEE SoutheastCon 2000.’Preparing for The New Millennium'(Cat. No. 00CH37105) (pp. 110-115). IEEE. He, J., Ding, L., Jiang, L., & Ma, L. (2014, July). Kernel ridge regression classification. In 2014 International Joint Conference on Neural Networks (IJCNN) (pp. 2263-2267). IEEE. Kale, S., & Prasad, R. (2018). Author identification on imbalanced class dataset of Indian literature in Marathi. International Journal of Computer Sciences and Engineering, 6, 54……

[1]William A. Ainsworth, “A System for Converting English Text into Speech”, IEEE Transactions on Audio and Electro-Acoustics, Vol. Au-21, No.3, pp. 288-290, Jun 1973.[2]Katsanobu Fushikida, Yukio Mitome and Yuji Inoue, “A Text To Speech Synthesizer for the Personal Computer”, IEEE Transactions on Consumer Electronics, Vol. CE-28, No. 3., pp. 250-256, August 1982.[3]Fu-Chiang Chou, Chiu-Yu Tseng and Lin-Shan Lee, “A Set of Corpus-Based Text-to-Speech Synthesis Technologies for Mandarin Chinese”, IEEE Transactions on Speech and Audio Processing, Vol. 10, No. 7, pp. 481 – 494, 2002. Speech to Text in Marathi[4]Marc Schroder, Jurgen Trouvain, “The German Text-to-Speech synthesis System MARY: A tool for Research Development and Teaching”, International Journal of Speech Technology, 6, pp.365-377, 2003.[5]Bhuvana Narasimhan, Richard Sproat and George Kiraz, “Schwa-Deletion in Hindi Text-to-Speech Synthesis”, International Journal of Speech Technology, Vol. 7, pp. 319-333, 2004.[6]Diemo Schwarz, “Concatenative sound synthesis: The early years”, Journal of New Music Research, Vol. 35, No. 1, pp. 3-22, 2006.[7]Jerorne R. Bellegarda, “Unit-Centric Feature Mapping for Inventory Pruning in Unit Selection Text-to-Speech Synthesis”, IEEE Transactions an Audio, Speech and Language Processing, Vol. 16, No. 01, PP. 74-82, Jan-2008.[8]S. D. Shirbahadurkar, D. S. Bormane, “Speech Synthesizer Using Concatenative Synthesis Strategy for Marathi language (Spoken in Maharashtra, India)”,International Journal of Recent Trends in Engineering, Vol. 2, No. 4, pp. 80-82, 2009.[9]Pamela Chaudhury, Madhuri Rao, KVinod Kumar, “Symbol Based Concatenation Approach for Text to Speech System for Hindi using Vowel Classification Technique”, IEEE, 2009 World Congress on Nature &Speech to Text in Marathi Biologically Inspired Computing (NaBIC 2009), pp. 1082-1087, 2009.[10]Naim R. Tyson and Ila Nagar, “Prosodic rules for schwa-deletion in hindi text-to-speech synthesis”, International Journal Speech Technology, Vol. 12, pp. 12-25, 2009.[11]Junichi Yamagishi and Keiichi Tokuda, “Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis”, IEEE Transactions on Audio, Speech and Language Processing, Vo……

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