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1、 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 medical transcriptionist . According to industry experts, at its inception, speech rec
2、ognition (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. Additionally, to be used effectively, it required changes to the ways
3、 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 dictation is highly interpretive and often requires judgment that may be
4、 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 artificial syntax systems which are usually domain-specific and natural
5、language processing which is usually language-specific. Each of these types of application presents its own particular goals and challenges.ApplicationsHealth careIn the health care domain, even in the wake of improving speech recognition technologies, medical transcriptionists (MTs) have not yet be
6、come 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 recognition can be implemented in front-end or back-end of the medical documentation process.Front-End SR is where the
7、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 document. It never goes through an editor.Back-End SR is where the provider dictates into a digital dictation system,
8、 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 the report. Deferred SR is being widely used in the industry currently.Many Electronic Medical Records (EMR) a
9、pplications can be more effective and may be performed more easily when deployed in conjunction with a speech-recognition 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
10、devoted in the last decade to the test and evaluation of speech recognition in fighter aircraft. Of particular note are the U.S. program in speech recognition for the Advanced Fighter Technology Integration (AFTI)/F-16 aircraft (F-16 VISTA), the program in France on installing speech recognition sys
11、tems on 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 coordina
12、tes 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 were
13、as follows:1. Speech recognition has definite potential for reducing pilot workload, but this potential was not realized consistently. 2. 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
14、tes, pilots would not use the system. 3. 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 e
15、xtendable to the cockpit, should improve the utility of speech recognition in high-performance aircraft.Working with Swedish pilots flying in the JAS-39 Gripen cockpit, Englund (2004) found recognition deteriorated with increasing G-loads. It was also concluded that adaptation greatly improved the r
16、esults 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 recognizer, as could be expected. A restricted vocabulary, and above all, a proper
