Research is very important in all aspects of our lives. We take for granted many things that resulted from research. There are many lifesaving discoveries based on research. There are other products of research that we take for granted and do not fully understand.
In 1966 Leonard Baum and Ted Petrie published a paper on Markov chains (Baum & Petrie, 1966). This work is generally referred to as a hidden Markov model. The paper built upon the research of others and laid the groundwork for future advancements. In 1975 Dr. James Baker used Baum and Petrie’s work to create a speech processing system called DRAGON (Rabiner, 1989). In 1982, he and his wife founded Dragon Systems. In 1997, Dragon Systems releases Dragon Naturally Speaking (Dragon). ScanSoft acquired Dragon Systems, which was in turn acquired by Nuance in 2005.
Google introduced experimental searching by voice in the early 2000’s (Franz & Milch, 2002). In 2006, Google released GOOG-411, a speech recognition service (Schuster, 2010). This service was a computerized version of directory assistance. In 2008, Google released Voice Search in the United States. This was similar to GOOG-411 other than it used the phone’s data network to transfer the audio instead of the phone’s audio line.
Apple released the iPhone 4S on October 24, 2011 (Murph, 2011). The iPhone 4S included a new feature named Siri (Apple, 2011). Siri was marketed as a digital personal assistant. Siri used Nuance’s technology to power Siri (Beasley, 2014).
This example demonstrates the power of research. Dr. Baker built upon the work of Doctors Baum and Petrie to create the foundation for technology that changed the way we interact with cell phones. Hidden Markov models have been used for a multitude of classification problems such as DNA sequencing (Nelson, Foo, & Weatherspoon, 2008), image processing (Kalavathy & Suresh, 2010), stock market prediction (Somani, Talele, & Sawant, 2014), and fraud detection (Iyer, Mohanpurkar, Janardhan, Rathod, & Sardeshmukh, 2011).
This is one example of how a research enriches our lives. It is a gradual process. This example spans fifty years. It reinforces the material covered in the text, and delivered elsewhere. There is a web of knowledge. A researcher looks for something that is not there, but should be. Doctors Baum and Petrie examined the work done previously on Markov chains and had insight into a new way to use them for classification. Doctor Baker used the work on hidden Markov models to address the problem of computerized speech recognition. The researchers at Google saw the problem of a user having to type search queries and developed a speech interface. Apple made it mainstream. So in answer to the question, is research important, ask Siri.
References
Apple. (2011). Retrieved from http://www.apple.com/pr/library/2011/10/04Apple-Launches-iPhone-4S-iOS-5-iCloud.html
Baum, L. E., & Petrie, T. (1966). Statistical inference for probabilistic functions of finite state Markov chains. The Annals of Mathematical Statistics, 37(6), 1554-1563. Retrieved from http://www.jstor.org/stable/2238772
Beasley, M. (2014). Why is Apple hiring Nuance engineers? Apparently to replace Siri’s Nuance-powered backend. Retrieved from http://9to5mac.com/2014/06/30/why-is-apple-hiring-nuance-engineers-apparently-to-replace-siris-nuance-powered-backend/
Dragon. History of speech and voice recognition and transcription software. Retrieved from http://www.dragon-medical-transcription.com/history_speech_recognition_timeline.html
Franz, A., & Milch, B. (2002). Searching the Web by voice. Paper presented at the Proceedings of the 19th international conference on Computational linguistics - Volume 2, Taipei, Taiwan.
Iyer, D., Mohanpurkar, A., Janardhan, S., Rathod, D., & Sardeshmukh, A. (2011, 11-14 Dec. 2011). Credit card fraud detection using Hidden Markov Model. Paper presented at the Information and Communication Technologies (WICT), 2011 World Congress on.
Kalavathy, S., & Suresh, R. M. (2010, 15-17 Dec. 2010). Image denoising using improved semantic approximation algorithm in wavelet domain hidden Markov model. Paper presented at the Signal and Image Processing (ICSIP), 2010 International Conference on.
Murph, D. (2011). iPhone 4S hands-on! Retrieved from http://www.engadget.com/2011/10/04/iphone-4s-hands-on/
Nelson, R., Foo, S., & Weatherspoon, M. (2008, 16-18 March 2008). Using hidden Markov modeling in DNA sequencing. Paper presented at the System Theory, 2008. SSST 2008. 40th Southeastern Symposium on.
Rabiner, L. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2), 257-286. doi:10.1109/5.18626
Schuster, M. (2010). Pricai 2010: Trends in artificial intelligence (M. A. O. Byoung-Tak Zhang Ed.): Springer.
Somani, P., Talele, S., & Sawant, S. (2014, 20-21 Dec. 2014). Stock market prediction using hidden Markov model. Paper presented at the Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International.
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