Editing Speech recognition (section)

===Military===

====High-performance fighter aircraft====
Substantial efforts have been devoted in the last decade to the test and evaluation of speech recognition in [[fighter aircraft]]. Of particular note have been the US program in speech recognition for the [[General Dynamics F-16 Fighting Falcon variants#F-16_Advanced_Fighter_Technology_Integration|Advanced Fighter Technology Integration (AFTI)]]/[[F-16]] aircraft ([[F-16 VISTA]]), the program in France for [[Mirage (aircraft)|Mirage]] aircraft, and other programs in the UK dealing with a variety of aircraft platforms. In these programs, speech recognizers have been operated successfully in fighter aircraft, with applications including setting radio frequencies, commanding an autopilot system, setting steer-point coordinates and weapons release parameters, and controlling flight display.

Working with Swedish pilots flying in the [[Saab JAS 39 Gripen|JAS-39]] Gripen cockpit, Englund (2004) found recognition deteriorated with increasing [[g-force|g-loads]]. The report also concluded that adaptation greatly improved the results in all cases and that the introduction of models for breathing was shown to improve recognition scores significantly. Contrary to what might have been expected, no effects of the broken English of the speakers were found. It was evident that spontaneous speech caused problems for the recognizer, as might have been expected. A restricted vocabulary, and above all, a proper syntax, could thus be expected to improve recognition accuracy substantially.<ref>{{Cite thesis |last=Englund |first=Christine |title=Speech recognition in the JAS&nbsp;39 Gripen aircraft: Adaptation to speech at different G-loads |degree=Masters thesis |publisher=[[Stockholm University|Stockholm Royal Institute of Technology]] |url=http://www.speech.kth.se/prod/publications/files/1664.pdf |year=2004 |url-status=live |archive-url=https://web.archive.org/web/20081002002102/http://www.speech.kth.se/prod/publications/files/1664.pdf |archive-date=2 October 2008 |df=dmy-all}}</ref>

The [[Eurofighter Typhoon]], currently in service with the UK [[RAF]], employs a speaker-dependent system, requiring each pilot to create a template. The system is not used for any safety-critical or weapon-critical tasks, such as weapon release or lowering of the undercarriage, but is used for a wide range of other cockpit functions. Voice commands are confirmed by visual and/or aural feedback. The system is seen as a major design feature in the reduction of pilot [[workload]],<ref>{{Cite web |title=The Cockpit |url=https://www.eurofighter.com/the-aircraft#cockpit |url-status=live |archive-url=https://web.archive.org/web/20170301222529/https://www.eurofighter.com/the-aircraft#cockpit |archive-date=1 March 2017 |website=Eurofighter Typhoon |df=dmy-all}}</ref> and even allows the pilot to assign targets to his aircraft with two simple voice commands or to any of his wingmen with only five commands.<ref>{{Cite web |title=Eurofighter Typhoon – The world's most advanced fighter aircraft |url=http://www.eurofighter.com/capabilities/technology/voice-throttle-stick/direct-voice-input.html |url-status=live |archive-url=https://web.archive.org/web/20130511025203/http://www.eurofighter.com/capabilities/technology/voice-throttle-stick/direct-voice-input.html |archive-date=11 May 2013 |access-date=1 May 2018 |website=www.eurofighter.com |df=dmy-all}}</ref>

Speaker-independent systems are also being developed and are under test for the [[Lockheed Martin F-35 Lightning II|F-35 Lightning II]] (JSF) and the [[Alenia Aermacchi M-346 Master]] lead-in fighter trainer. These systems have produced word accuracy scores in excess of 98%.<ref>{{Cite web |last=Schutte |first=John |date=15 October 2007 |title=Researchers fine-tune F-35 pilot-aircraft speech system |url=https://www.af.mil/News/story/id/123071861/ |url-status=live |archive-url=https://web.archive.org/web/20071020030310/http://www.af.mil/news/story.asp?id=123071861 |archive-date=20 October 2007 |publisher=United States Air Force}}</ref>

====Helicopters====
The problems of achieving high recognition accuracy under stress and noise are particularly relevant in the [[helicopter]] environment as well as in the jet fighter environment. The acoustic noise problem is actually more severe in the helicopter environment, not only because of the high noise levels but also because the helicopter pilot, in general, does not wear a [[Fighter pilot helmet|facemask]], which would reduce acoustic noise in the [[microphone]]. Substantial test and evaluation programs have been carried out in the past decade in speech recognition systems applications in helicopters, notably by the [[U.S. Army]] Avionics Research and Development Activity (AVRADA) and by the Royal Aerospace Establishment ([[Royal Aircraft Establishment|RAE]]) in the UK. Work in France has included speech recognition in the [[Puma helicopter]]. There has also been much useful work in [[Canada]]. Results have been encouraging, and voice applications have included: control of communication radios, setting of [[navigation]] systems, and control of an automated target handover system.

As in fighter applications, the overriding issue for voice in helicopters is the impact on pilot effectiveness. Encouraging results are reported for the AVRADA tests, although these represent only a feasibility demonstration in a test environment. Much remains to be done both in speech recognition and in overall [[speech technology]] in order to consistently achieve performance improvements in operational settings.

====Training air traffic controllers====
Training for air traffic controllers (ATC) represents an excellent application for speech recognition systems. Many ATC training systems currently require a person to act as a "pseudo-pilot", engaging in a voice dialog with the trainee controller, which simulates the dialog that the controller would have to conduct with pilots in a real ATC situation. Speech recognition and [[speech synthesis|synthesis]] techniques offer the potential to eliminate the need for a person to act as a pseudo-pilot, thus reducing training and support personnel. In theory, Air controller tasks are also characterized by highly structured speech as the primary output of the controller, hence reducing the difficulty of the speech recognition task should be possible. In practice, this is rarely the case. The FAA document 7110.65 details the phrases that should be used by air traffic controllers. While this document gives less than 150 examples of such phrases, the number of phrases supported by one of the simulation vendors speech recognition systems is in excess of 500,000.

The USAF, USMC, US Army, US Navy, and FAA as well as a number of international ATC training organizations such as the Royal Australian Air Force and Civil Aviation Authorities in Italy, Brazil, and Canada are currently using ATC simulators with speech recognition from a number of different vendors.{{citation needed|date=December 2012}}