计算机网络报告模板

计算机网络报告模板

《计算机网络》

报告

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计算机网络报告模板

Speech recognition

History

One 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 . 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. Additionally, 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 dictation 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 "artificial 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.

Applications

Health care

In the domain, 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 recognition 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 document. 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 - 2 -

计算机网络报告模板

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 (EMR) applications 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.

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 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 systems 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 coordinates 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 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 rates, 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 extendable 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 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 recognizer, as could be expected. A restricted vocabulary, and

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计算机网络报告模板

above all, a proper syntax, could thus be expected to improve recognition accuracy

substantially.

The Eurofighter Typhoon currently in service with the UK 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 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, and even allows the pilot to assign targets to himself with two simple voice commands or to any of his wingmen with only five

commands.

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