The document discusses how speech technologies can be used to increase productivity, reduce waste, and lower costs in industrial processes and information technology. It argues that speech recognition and natural language processing will have major impacts over the next 15 years. It also summarizes several references on speech technologies and their applications.

1. Prof. R.MANOHARAN A Harbinger of e-waste : Waste controlled through Industrial Process & Information Technology by using Speech Technologies . SNS College of Technology - Coimbatore - INDIA

2. Speech and natural language understanding are the key technologies that will have the most impact in the next 15 years Bill Gates Chairman and Chief Architect, Microsoft corporation

3. Production Productivity Waste Reduction Cost Control Cost Reduction Input Output Value Analysis and Value Engineering Using Speech Technolgies To Consumer.. The output is Networked & Optimized

4. Five dominant infotrends are interrelated and mutually reinforcing.

5. Content : A product / A Solution / A Solution oriented Product / A Business Alliance Interoperability : 100% exchange (The content shared from peer-to-peer, there must be 100% shareable or exchangeable with out loosing its dense). Disintermediation: Known delays are avoided (In the peer-to-peer transit, the delays, in Technology of Hardware, Software, Middleware, Netware, Intermediaries, Brokers, Agents are to be avoided). Globalization : Universal Standardization (optimization & network) (Cutting across the barrier of races, geographical area , currency conversion, laws of different nations etc., when person availing the Business and Information services). Convergence : Gateway for the next layer is of the service level when the content passes through peer-to-peer, the information technology and the business elements creates a gateway for a new content (re-engineered) to develop or to modify the Business resources to dynamically suit the society .

7. [1] . Bill Gates – Chairman and Chief Architect, Microsoft corporation.- Microsoft Speech Server VISION – Introduction CD-ROM- Part No. 098-97420 – 2004. [2]. Harvey. L. Poppel, Bernard Goldstein, 1987, “Information Technology-The Trillion Dollar Opportunity”, McGraw-Hill International Editions, Management Series. ISBN:0-07-050511-X p.3-8 [3]. Suhm, B. and P. Peterson, 2002. A data-driven methodology for evaluating and optimizing call center IVRs. Int. J. Speech Technol., 5: 23-37. DOI:10.1023/A:1013674413897 [4]. Olaszi, P., I. Koutny and S.L. Kálmán, 2002. From bliss symbols to grammatically correct voice output: A communication tool for people with disabilities. Int. J. Speech Technol., 5: 49-56. DOI:10.1023/A:1013682632553 [5]. Fogel, N., 2002, A commercial implementation of free-speech speaker verification system in a call center. Int. J. Speech Technol., 5: 313-320. DOI:10.1023/A:1020956924277 [6]. Plomp, C.J. and O. Mayora-Ibarra, 2002. A generic widget vocabulary for the generation of graphical and speech-driven user interfaces. Int. J. Speech Technol., 5: 39-47. DOI:_ 10.1023/A:1013678514806 [7]. Manoharan R (author self reference), Dr.K.Vivekanandan, & Dr.V. Sundaram, Journal of Computer Science 5 (2): 90-96, 2009 ISSN 1549-3636 © 2009 Science Publications.(An International Journal) - DOI: http:// www.scipub.org/scipub/detail_issue.php?V_No =43&j_id= jcs [8]. Aaron Fisher, 2009. A natural part of natural language. http://www.speechtechmag.com/Articles/Column/Inside-Outsourcing/A-Natural-Part-of-Natural-Language-52492.aspx REFRENCES