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Communications between Pilots and Air Traffic Controllers in Digital Readouts - Research Paper Example

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The paper "Communications between Pilots and Air Traffic Controllers in Digital Readouts" states that completely natural, continuous speech engrosses a massive deal of “co-eloquent”, where adjacent words function jointly without pauses or any other clear separation between words…
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Communications between Pilots and Air Traffic Controllers in Digital Readouts
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?Displaying Communications between Pilots and Air Traffic Controllers in Digital Readouts Insert Able Flight Able Flight refers to a nonprofit scholarship organization, which works with flight institutions that issue the training. The organization is supported via generous donation of people, corporate sponsorships and foundation funding. Note that Able Flight organization operates under the IRS principles and policies, and the donations it receives are levy deductible to the full-stretch of the law. The ultimate objective of Able Flight program is to assist the disabled or handicapped individuals to acquire the aptitude to fly an airplane. This is because different types of disabilities needs distinct solutions to assist them fly airplanes. Note that despite the fact that the program fundamentally helps the disabled people, it also assists normal people who have passion and interest of flying airplanes but do not have the ability. The ultimate aim of this context is to examine how Able Flight program helps the disabled individuals to fly airplanes as well as to provide solutions following the difficulties encountered in flight training. It winds up by examining the implementation process of a voice recognition technology in pilot’s communication (Karat, Vergo and Nahamoo 2007). How Able Flight Helps Disabled People to Fly Airplanes Just as mentioned, the Able Flight program does not offer flight training or classes. However, it is involved in teaching flight related life lessons that make the participants good pilots and flight attendants. The organization corporate with different flight schools among them being Purdue University campus. Able Flight has been associating with this university for two years in a row where it has brought four scholars to the campus to be educated on how to fly. Each of them has physical disability that, up to present day, has prevented them from undertaking an interest or career in aviation. Nevertheless, with the assistance from special aircraft and scholarships from Able Flight, the scholars have been able to acquire light sport pilot certificates after exhaustive five-week training period. According to Geoff Aschenberger, “The most interesting part of it is that these scholars are able to cover the whole package in one month while the Purdue flight scholars take five to six months to cover”. Due to the density of the schedule at Purdue, the scholars and flight instructors take most of their time at the airport in the classroom and in their specially modeled aircraft. A partial day engross an early morning arrival, 90 minutes of flying, debate, more flying and landings, lunchtime meals, even intense flying and ground institute lessons. Note that all these things take place at the Purdue University campus flight school. That does not mean the Able Flight has no role that it plays. As far as those disabled scholars are concerned, Able Flight must participate or take part in ensuring that they obtain exactly what they went to acquire. The organizational program is developed in a way that it has to follow up the students’ progress, know their strong points and motivate them to keep it up; identify their weak points and help them both find permanent solutions to them in order to make sure they progress. Generally, Able Flight makes follow up on all the disabled students it gives scholarships and makes sure they are safe and healthy. The school included time for social time where some of the Able Flight staff goes there to spend sometimes with them as well as join them with the other flight students so that they can feel accepted and embraced in the community. The school’s training personnel also help the disabled students to participate in school’s activities and to mingle with others so that they do not feel lonely or rejected. Besides, the school’s staff and Able Flight made it possible for the students to live together in First Street Towers, which is a university’s owned dwelling hall. Whereas the Able Flight scholars continue learning to fly, the flight instructors also learn new techniques of teaching and concerning conquering adversity. Derek Stewart, a Purdue flight scholar and verified flight instructor stated that, “I wanted to get out of my comfort zone. I thought it would be a problem for me and a challenge to my teaching skills.” He added on that “Even within the first two weeks, I was able to see them develop as people and as pilots.” Therefore, other than just sponsoring and giving the disabled students scholarships, Able Flight give them full support in terms of both financial and mental support. Implementation of the Voice Recognition Technology for Communication Voice recognition refers to the process of taking the uttered word as an input to a computer program. This procedure is significant to practical reality since it issues a fairly native and intuitive means of managing the simulation while permitting the hand of the user to remain free (Junqua and Haton 2005). Therefore, it is important to understand the concept of voice recognition in the field of practical reality, and look at the way voice recognition is achieved. Voice Recognition and its Importance to a Virtual Environment Voice recognition refers to the technique through which sounds, words and phrases uttered by individuals are changed into electrical signals, and these indications are distorted into coding prototypes to which meaning has been allocated (Karat, Vergo and Nahamoo 2007). Despite the fact that the issue could more generally be termed as “sound recognition”, the main concentration here is on human voice since individuals most frequently and most naturally employ their voices to converse their notions to others in their immediate environments. In case of a virtual surrounding, the user would most probably acquire the greatest feeling of immersion, or being part of the imitation, if they could employ their ordinary form of conversing, the voice (Pierce 2006). The challenge in using voice as a computer imitation depends on the distinctions between human speech and the more ancient means of computer input. Whereas computer programs are usually modeled to generate specific and well described response after acquiring the appropriate input, the human voice and uttered words can have distinct meanings if uttered with distinct infections or in distinct contexts. Numerous advances have been attempted, with ranging degrees of triumph, to conquer these challenges (Giovanni, Varile and Zampolli 2000). How Voice Recognition is Performed The most usual approaches to voice recognition can be categories into two major groups: template matching and feature analysis (Junqua and Haton 2005). Template matching is the easiest method and has an elevated accuracy when employed efficiently, but it also endures the most limitations. Just like any other approach to voice recognition, the initial stage is for the user to utter a word or phrase into a microphone. The electrical indication from the microphone is digitize by an “analog-to-digital (A/D) converter”, and is kept in memory. To establish the “meaning” of this voice input into the computer, the computer tries to equal the input within a digitized voice sample, or template, which has a recognized meaning. This method is a close analogy to the customary rule inputs from a keyboard. The program engrosses the input template and tries to equal this template with the real input using an easy condition statement (Karat, Vergo and Nahamoo 2007). Since every person has a distinct voice, the program is not able to carry a template for every possible user, meaning that the program has to be trained first to adopt to new users’ voice inputs before the program can actually identify the user’s voice. During a learning session, the program shows a printed word or phrase, and the user utters that word or phrase numerous times into a microphone (Giovanni, Varile and Zampolli 2000). The program calculates a statistical mean of the multiple samples of similar word and keeps the averaged sample as a template in a program data arrangement. With this kind of coming close to voice recognition, the program has a vocabulary that is restrained to the users who have learned the program. The good part of voice recognition is the fact that both disabled flight students and normal flight students can use it because the technique is not only efficient in the field of airplanes, but also in other fields (Pierce 2006). Therefore, the fact that Able Flight supports and encourages flight students to use it shows that its program is much helpful to both the disabled students and the normal students at flight schools recognized by Able Flight program. A more usual way of voice recognition is present through feature analysis and this method normally causes “speaker-independent” voice recognition (Junqua and Haton 2005). As an alternative, of attempting to obtain an exact or near-specific equality between the real voice input and a prior stored voice template, this technique initially processes the voice input using “Fourier transforms” or “linear prognostic coding (LPC)”, then tries to acquire characteristics likeliness between the anticipated inputs and the real voice input. This likeliness will provide a broadened variety of speakers, and therefore, the scheme does not require to be educated by every new user (Karat, Vergo and Nahamoo 2007). The kinds of speech distinctions that the speaker-independent technique can tackle them, but which pattern equivalent would not properly tackle, engross accents, and ranging speed of delivery, pitch, inflection and volume. Speaker-independent speech recognition has proven to be very challenging, with some of the massive obstacles being the range of accents and infections employed by speakers of distinct similarities. Recognition exactness for speaker-independent schemes is rather little than for the speaker-dependent schemes, often between 90 and 95 percent. Another crucial means of distinguishing between voice recognition schemes is through establishing if they can take care of only distinct vocabularies, linked words, or continuous speech (Junqua and Haton 2005). In fact, numerous voice recognition schemes are discrete word schemes, and these are simplest to put into practice. For this kind of scheme, the speaker must pause between words. This is proper for circumstances where the user is need to issue only a single word responses or principles, but is very abnormal for several word inputs (Karat, Vergo and Nahamoo 2007). In a linked word voice recognition scheme, the user is permitted to utter in numerous word phrases, but he or she has to be very keen to eloquent each word and not smear the end of one word into the starting of the next word. Completely natural, continuous speech engrosses a massive deal of “co-eloquent”, where adjacent words functions jointly without pauses or any other clear separation between words (Pierce 2006). Therefore, it is clear that different types of speeches respond differently to the voice recognition. This technique is very helpful in communication and the fact that Able Flight mostly deals with disabled people makes it even interesting into the airplane field (Giovanni, Varile and Zampolli 2000). Bibliography Karat, C.; Vergo, J.; Nahamoo, D., 2007. "Conversational Interface Technologies". Lawrence Erlbaum Associates Inc. ISBN 978-0805858709.  Giovanni Battista Varile, Antonio Zampolli, 2000, Survey of the state of the art in human language technology. Cambridge Studies In Natural Language Processing. XII–XIII. Cambridge University Press. ISBN 0-521-59277-1  Junqua, J.-C.; Haton, J.-P. 2005, Robustness in Automatic Speech Recognition: Fundamentals and Applications. Kluwer Academic Publishers. ISBN 978-0792396468. Pierce J., 2006, "Whither Speech Recognition". Journal of the Acoustical Society of America. Read More
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