Mobile phone usage in World is spreading rapidly and has gone through great changes due to new developments and innovations in mobile phone technology. This project based on evaluating voice versus keypad as a means for entry and editing of texts. In other words, messages can be voice/speech typed. The project will make use of a dictating-machine prototype for the English language, which recognizes in real time natural-language sentences built from a 2000 word vocabulary. A speech to text converter is developed to send SMS .It is found that large-vocabulary speech recognition can offer a very competitive alternative to traditional text entry.

1. Andreas Stolcke, , Barry Chen, Horacio Franco, Venkata Ramana Rao Gadde, Martin Graciarena, , Mei-Yuh Hwang, Katrin Kirchhoff, , Arindam Mandal, Nelson Morgan, , Xin Lei, Tim Ng, Mari Ostendorf, Kemal Sönmez, Anand Venkataraman, Dimitra Vergyri, and Qifeng Zhu, ?Recent Innovations in Speech-to-Text Transcription at Sri-icsi-uw? IEEE Transactions On Audio, Speech, And Language Processing, vol. 14, no. 5, september 2006, pp 1729-1744
2. Brandon Ballinger, Cyril Allauzen, Alexander Gruenstein, Johan Schalkwyk, ?On-Demand Language Model Interpolation for Mobile Speech Input?, INTERSPEECH 2010, 26-30 September 2010, Makuhari, Chiba, Japan, pp 1812-1815
3. Ryuichi Nisimura, Jumpei Miyake, Hideki Kawahara and Toshio Irino, ?Speech-To-Text Input Method For Web System Using Javascript?, IEEE SLT 2008 pp 209-212
4. M. Tomalin, F. Diehl, M.J.F. Gales, J. Park & P.C. Woodland , ?Recent Improvements To The Cambridge Arabic Speech-To-Text Systems?, ICASSP 2010 pp 4382-4385
5. Janet See, Umi Kalsom Yusof, Amin Kianpisheh, ?User Acceptance towards a Personalised Handsfree Messaging Application (iSay-SMS)?, CSSR 2010 Initial Submission December 5-7,2010 pp 1165-1170
6. Panikos Heracleous, Hiroshi Ishiguro and Norihiro Hagita, ?Visual-speech to text conversion applicable to telephone communication for deaf individuals? 18th International Conference on Telecommunication 2011. pp 130-133
7. Y. Liu, E. Shriberg, A. Stolcke, D. Hillard, M. Ostendorf, and M. Harper, ?Enriching speech recognition with automatic detection of sentence boundaries and disfluencies,? IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 5, pp. 1524–1538, Sep. 2006.
8. M.J.F Gales, F. Diehl, C.K. Raut, M. Tomalin, P.C. Woodland, and K. Yu, ?Development of a phonetic system for large vocabulary arabic speech recognition,? in Proc. of ASRU, 2007.
9. L. Nguyen, T. Ng, K. Nguyen, R. Zbib, and J. Makhoul, ?Lexical and phonetic modeling for arabic automatic speech recognition,?in Proc. of Interspeech, 2009.
10. C.C. Wong, ?Enabling Ecosystem for Mobile Advertising in an Emerging Economy,? Monash University Doctoral Colloquium. Langkawi, Kedah, Malaysia, 14-16 December 2009.
11. G. Potamianos, C. Neti, G. Gravier, A. Garg, and A.W. Senior, ?Recent advances in the automatic recognition of audiovisual speech,? in Proceedings of the IEEE, vol. 91, Issue 9, pp. 1306–1326, 2003.
12. A. V. Nefian, L. Liang, X. Pi, L. Xiaoxiang, C. Mao, and K. Murphy, ?A coupled hmm for audio-visual speech recognition,? in Proceedings of ICASSP 2002, 2002.
13. Garg, Mohit. Linear Prediction Algorithms. Indian Institute of Technology, Bombay, India, Apr 2003.
14. Li, Gongjun and Taiyi Huang. An Improved Training Algorithm in Hmm-Based Speech Recognition. National Laboratory of Pattern Recognition. Chinese Academy of Sciences, Beijing.
15. M. Abe, S. Nakamura, K. Shikano, and H. Kuwabara,"Voice conversion through vector quantization," in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, pp. 655-658, IEEE, April 1988
16. M.J.F Gales, F. Diehl, C.K. Raut, M. Tomalin, P.C. Woodland, and K. Yu,?Development of a phonetic system for large vocabulary arabic speech recognition,? in Proc. of ASRU, 2007.
17. L. Nguyen, T. Ng, K. Nguyen, R. Zbib, and J. Makhoul, ?Lexical and phonetic modeling for arabic automatic speech recognition,? in Proc. of Interspeech, 2009.

Short Message Service (SMS) speech acquisition Hidden Markov Model (HMM) HMM-based recognition.