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Artificial Intelligence, Expert Systems and Robotics

Evaluating natural language and voice recognition systems

  • 3 things to know
  • A2 Unit 1

Overview

How voice interfaces improve accessibility and why recognition accuracy falls in a noisy environment.

What you need to know

Answer each one before you reveal it.

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Key term

Why does dictated text still have to be proofread?

Key term

Give an overall judgement on where voice and natural language interfaces are best used.

Key term

Explain how voice interfaces improve accessibility.

Questions from this subtopic

Each one with the model answer underneath.

  1. 1

    Explain how voice interfaces improve accessibility.

    Model answer

    Voice interfaces let people with limited hand movement or impaired sight operate a computer, dictate documents and control devices without needing a keyboard, a mouse or a screen.

  2. 2

    Give an occupational situation where a hands-free voice interface is a real advantage.

    Model answer

    A warehouse picker with both hands full can be given the next location by voice and confirm the pick by speaking, which would be impossible with a handheld terminal.

  3. 3

    Why is dictation faster than typing for most users?

    Model answer

    Most people speak several times faster than they type, so dictation produces a first draft of a document more quickly even allowing for the corrections that follow.

  4. 4

    State one advantage of a natural language interface over a query language.

    Model answer

    A natural language interface needs no training in command syntax, because the user asks the question in ordinary English rather than learning how to write a query.

  5. 5

    How does a voice system reduce the cost of handling telephone enquiries?

    Model answer

    A voice system answers or routes routine telephone enquiries automatically and handles many callers at the same time, so staff are needed only for the calls that fall outside it.

  6. 6

    Explain why recognition accuracy falls in a noisy environment.

    Model answer

    Background sound is captured and sampled along with the speech, so the acoustic matching is working on a mixed signal and the recogniser confuses or misses phonemes.

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