计算机网络报告模板

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2、earbook of zhuanglang already prepared draft, entered the phase of evaluation. Civil air defense workPAGE 12County continuation records has examined and approved the draft, spirit, believe, comprehensive Yearbook of zhuanglang already prepared draft, entered the phase of evaluation. Civil air defens

3、e work 计算机网络报告题目： 出处： 班级： 学号： 姓名： Speech recognitionHistoryOne of the most notable domains for the commercial application of speech recognition in the United States has been health care and in particular the work of the HYPERLINK /wiki/Medical_transcription o Medical transcription medical transcript

4、ionist . According to industry experts, at its inception, speech recognition (SR) was sold as a way to completely eliminate transcription rather than make the transcription process more efficient, hence it was not accepted. It was also the case that SR at that time was often technically deficient. A

5、dditionally, to be used effectively, it required changes to the ways physicians worked and documented clinical encounters, which many if not all were reluctant to do. The biggest limitation to speech recognition automating transcription, however, is seen as the software. The nature of narrative dict

6、ation is highly interpretive and often requires judgment that may be provided by a real human but not yet by an automated system. Another limitation has been the extensive amount of time required by the user and/or system provider to train the software.A distinction in ASR is often made between arti

7、ficial syntax systems which are usually domain-specific and natural language processing which is usually language-specific. Each of these types of application presents its own particular goals and challenges.ApplicationsHealth careIn the HYPERLINK /wiki/Health_care o Health care health care domain,

8、even in the wake of improving speech recognition technologies, medical transcriptionists (MTs) have not yet become obsolete. Many experts in the field anticipate that with increased use of speech recognition technology, the services provided may be redistributed rather than replaced.Speech recogniti

9、on can be implemented in front-end or back-end of the medical documentation process.Front-End SR is where the provider dictates into a speech-recognition engine, the recognized words are displayed right after they are spoken, and the dictator is responsible for editing and signing off on the documen

10、t. It never goes through an editor.Back-End SR is where the provider dictates into a digital dictation system, and the voice is routed through a speech-recognition machine and the recognized draft document is routed along with the original voice file to the editor, who edits the draft and finalizes

11、the report. Deferred SR is being widely used in the industry currently.Many HYPERLINK /wiki/Electronic_Medical_Records o Electronic Medical Records Electronic Medical Records (EMR) applications can be more effective and may be performed more easily when deployed in conjunction with a speech-recognit

12、ion engine. Searches, queries, and form filling may all be faster to perform by voice than by using a keyboard.MilitaryHigh-performance fighter aircraftSubstantial efforts have been devoted in the last decade to the test and evaluation of speech recognition in fighter aircraft. Of particular note ar

13、e the U.S. program in speech recognition for the Advanced Fighter Technology Integration (AFTI)/ HYPERLINK /wiki/F-16 o F-16 F-16 aircraft ( HYPERLINK /wiki/F-16_VISTA o F-16 VISTA F-16 VISTA), the program in France on installing speech recognition systems on HYPERLINK /wiki/Mirage_(aircraft) o Mira

14、ge (aircraft) Mirage aircraft, and 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 co

15、ordinates and weapons release parameters, and controlling flight displays. Generally, only very limited, constrained vocabularies have been used successfully, and a major effort has been devoted to integration of the speech recognizer with the avionics system.Some important conclusions from the work

16、 were as follows:Speech recognition has definite potential for reducing pilot workload, but this potential was not realized consistently. Achievement of very high recognition accuracy (95% or more) was the most critical factor for making the speech recognition system useful with lower recognition ra

17、tes, pilots would not use the system. More natural vocabulary and grammar, and shorter training times would be useful, but only if very high recognition rates could be maintained. Laboratory research in robust speech recognition for military environments has produced promising results which, if exte

18、ndable to the cockpit, should improve the utility of speech recognition in high-performance aircraft.Working with Swedish pilots flying in the HYPERLINK /wiki/JAS-39 o JAS-39 JAS-39 Gripen cockpit, Englund (2004) found recognition deteriorated with increasing G-loads. It was also concluded that adap

19、tation greatly improved the results in all cases and introducing models for breathing was shown to improve recognition scores significantly. Contrary to what might be expected, no effects of the broken English of the speakers were found. It was evident that spontaneous speech caused problems for the

20、 recognizer, as could be expected. A restricted vocabulary, and above all, a proper syntax, could thus be expected to improve recognition accuracy substantially.The HYPERLINK /wiki/Eurofighter_Typhoon o Eurofighter Typhoon Eurofighter Typhoon currently in service with the UK HYPERLINK /wiki/RAF o RA

21、F RAF employs a speaker-dependent system, i.e. it requires 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 HYPERLINK /wiki/Cockpit o Cockpit cockpi

22、t 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 HYPERLINK /wiki/Workload o Workload workload, and even allows the pilot to assign targets to himself with two simple voice commands or to any of his wingm

23、en with only five commands. HelicoptersThe problems of achieving high recognition accuracy under stress and noise pertain strongly to the helicopter environment as well as to the fighter environment. The acoustic noise problem is actually more severe in the helicopter environment, not only because o

24、f the high noise levels but also because the helicopter pilot generally does not wear a 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

25、by the U.S. Army Avionics Research and Development Activity (AVRADA) and by the Royal Aerospace 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

26、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, alt

27、hough these represent only a feasibility demonstration in a test environment. Much remains to be done both in speech recognition and in overall speech recognition technology, in order to consistently achieve performance improvements in operational settings.Battle managementBattle management command

28、centres generally require rapid access to and control of large, rapidly changing information databases. Commanders and system operators need to query these databases as conveniently as possible, in an eyes-busy environment where much of the information is presented in a display format. Human machine

29、 interaction by voice has the potential to be very useful in these environments. A number of efforts have been undertaken to interface commercially available isolated-word recognizers into battle management environments. In one feasibility study, speech recognition equipment was tested in conjunctio

30、n with an integrated information display for naval battle management applications. Users were very optimistic about the potential of the system, although capabilities were limited.Speech understanding programs sponsored by the Defense Advanced Research Projects Agency (DARPA) in the U.S. has focused

31、 on this problem of natural speech interface. Speech recognition efforts have focused on a database of continuous speech recognition (CSR), large-vocabulary speech which is designed to be representative of the naval resource management task. Significant advances in the state-of-the-art in CSR have b

32、een achieved, and current efforts are focused on integrating speech recognition and natural language processing to allow spoken language interaction with a naval resource management system.Training air traffic controllersTraining for military (or civilian) air traffic controllers (ATC) represents an

33、 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 which the controller would have to conduct with pilots in a real ATC situation. Spe

34、ech recognition and synthesis techniques offer the potential to eliminate the need for a person to act as pseudo-pilot, thus reducing training and support personnel. Air controller tasks are also characterized by highly structured speech as the primary output of the controller, hence reducing the di

35、fficulty of the speech recognition task.The U.S. Naval Training Equipment Center has sponsored a number of developments of prototype ATC trainers using speech recognition. Generally, the recognition accuracy falls short of providing graceful interaction between the trainee and the system. However, t

36、he prototype training systems have demonstrated a significant potential for voice interaction in these systems, and in other training applications. The U.S. Navy has sponsored a large-scale effort in ATC training systems, where a commercial speech recognition unit was integrated with a complex train

37、ing system including displays and scenario creation. Although the recognizer was constrained in vocabulary, one of the goals of the training programs was to teach the controllers to speak in a constrained language, using specific vocabulary specifically designed for the ATC task. Research in France

38、has focused on the application of speech recognition in ATC training systems, directed at issues both in speech recognition and in application of task-domain grammar constraints. The USAF, USMC, US Army, and FAA are currently using ATC simulators with speech recognition from a number of different ve

39、ndors, including UFA, Inc. , and Adacel Systems Inc (ASI). This software uses speech recognition and synthetic speech to enable the trainee to control aircraft and ground vehicles in the simulation without the need for pseudo pilots.Another approach to ATC simulation with speech recognition has been

40、 created by Supremis. The Supremis system is not constrained by rigid grammars imposed by the underlying limitations of other recognition strategies.Telephony and other domainsASR in the field of telephony is now commonplace and in the field of computer gaming and simulation is becoming more widespr

41、ead. Despite the high level of integration with word processing in general personal computing, however, ASR in the field of document production has not seen the expected increases in use.The improvement of mobile processor speeds made feasible the speech-enabled Symbian and Windows Mobile Smartphone

42、s. Current speech-to-text programs are too large and require too much CPU power to be practical for the Pocket PC. Speech is used mostly as a part of User Interface, for creating pre-defined or custom speech commands. Leading software vendors in this field are: Microsoft Corporation (Microsoft Voice

43、 Command); Nuance Communications (Nuance Voice Control); Vito Technology (VITO Voice2Go); Speereo Software (Speereo Voice Translator). MyCaption for BlackBerry .People with DisabilitiesPeople with disabilities are another part of the population that benefit from using speech recognition programs. It

44、 is especially useful for people who have difficulty with or are unable to use their hands, from mild repetitive stress injuries to involved disabilities that require alternative input for support with accessing the computer. In fact, people who used the keyboard a lot and developed HYPERLINK /wiki/

45、Repetitive_Strain_Injury o Repetitive Strain Injury RSI became an urgent early market for speech recognition. Speech recognition is used in HYPERLINK /wiki/Deaf o Deaf deaf HYPERLINK /wiki/Telephony o Telephony telephony, such as HYPERLINK /wiki/Spinvox o Spinvox spinvox voice-to-text voicemail, HYP

46、ERLINK /wiki/Relay_services o Relay services relay services, and HYPERLINK /wiki/Telecommunications_Relay_Service l Captioned_telephone o Telecommunications Relay Service captioned telephone. Individuals with learning disabilities who have problems with thought to paper communication (essentially th

47、ey think of an idea but it is processed incorrectly causing it to end up differently on paper) can benefit from the software as it helps to overlap that weakness.语音识别发展历史商业应用的语音识别在美国是保健和medical transcriptionist等最显著的领域之一 。据业界专家称，在其成立以来，语音识别（简称SR）是为了彻底消除转录，而不是使转录过程更有效率，因此是不能接受的。也有人认为，SR在那个时候往往是在技术上缺乏。

48、此外，为了有效地加以利用，它需要改变工作方式和记录医师临床实践，其中甚至有许多不是所有的人愿意做的事。然而，语音识别自动化转录，被看作是该软件最大的限制。记叙一件事的本质是在听写时非常需要解释和判断，这需要一个真正的人，而不是通过自动化系统。另一个限制是用户和或系统供应商，培训软件所需的时间普遍的比较长。 ASR之间的区分往往是特定领域的“人工语法系统”和特定于语言的“自然语言处理”。所有这些类型的应用都有自己的特定目标和挑战。应用卫生保健在卫生保健领域，即使语音识别技术不断改进，medical transcriptionists （ MTS ）还是不会过时。许多该领域的专家预测，随着语音识别

49、技术的广泛使用，MTS提供的服务可能会重新分配，而不是取代。语音识别可以在医疗文件的进程前端或后端实施。SR的前端是要求供应商装入语音识别引擎，在他们说完话后正确显示出来，使用者负责编辑，并签署了有关文件。它从未审阅编辑。后端SR是提供者装入一个数字听写转换系统的地方，声音通过语言识别机器寻址，并且被认可的草案与原始的声音文件一起给编辑者，编辑草稿并且完成报告。 延期的SR是在当前产业用途广泛。当部署与语言识别引擎一道，许多电子病历(EMR)应用是更加有效的，并且也更加容易地执行。查寻、询问和填表全部由声音执行比通过使用键盘更快速。军事高性能战斗机在过去十年中我们都花了大量的努力来测试和评价语

50、音识别的战斗机。特别值得注意的是，美国计划为先进战斗机（ AFTI ） / F - 16战斗机（ F - 16型Vista ）安装语音识别的集成技术，法国也计划在幻影飞机安装语音识别系统，英国计划安装在不同的飞机平台。这些程序中，成功在战斗机中应用语音识别的包括：设置无线电频率，指挥一个自动系统，设置引导点坐标和武器释放参数，并控制飞行显示器。通常，只非常顺利地使用了有限，拘束的词汇量，并且主要努力致力于语音识别与航空电子学系统的综合化。一些重要结论的工作如下：1.语音识别具有一定的潜力，减少飞行员的工作量，但这种潜力始终没能实现。2.实现非常高的识别率（ 95 或以上）是使语音识别系统有用和

51、识别速率降低的最关键因素，飞行员不会使用该系统。3.更自然的词汇和语法，和更短的培训时间将是有益的，但前提是非常高的识别率可维持不变。实验室研究的在军事环境中抗噪语音识别产生了可喜的成果，如果扩展到驾驶舱，应能改进应用语音识别的高性能飞机。在JAS-39 Gripen驾驶舱内的瑞典飞行员 Englund (2004)发现了公认恶化随着G过载。 也结束适应在所有的情况下很大地改进了结果，并且介绍呼吸的模型显示极大改进公认比分。相反，可以预期，没有任何作用的蹩脚的英语发言者被发现。 很明显，可以预期，造成问题的自发讲话的语音识别。 受限的词汇，最重要的是，一个适当的语法，能因而期望极大地改进公认准

52、确性。目前在英国皇家空军拥有扬声器依赖系统欧洲台风，它要求每个试点创建一个模板。该系统不作任何安全关键或核武器的关键任务，如核武器释放或降低脚架，但广泛应用于其他驾驶舱职能。语音指令通过视觉和听觉反馈来确认。该系统被看作是一个主要的设计功能，减少飞行员的工作量，甚至可以以自己的两个简单的语音命令，或任何与他的飞行员只有五个命令改变试点的目标。直升机在高压和强烈噪音干扰的直升机环境实现高识别率的问题和战斗机环境一眼好。实际上，在直升机的环境，噪音问题更为严重，不仅是因为高噪音水平，而且还因为，直升机飞行员一般不戴减少麦克风噪音的口罩。语音识别系统在过去十年中已经进行了大量的试验和评估程序并应用在直升机，特别是美国陆军航空电子研究和发展活动（