Essay On Artificial Intelligence For Speech Recognition

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Artificial Intelligence For Speech Recognition

Abstract Artificial intelligence system for speech recognition is the science and engineering of making intelligent machines, especially intelligent computer programs. Some of its applications are game playing, speech recognition, understanding natural language, computer vision, expert systems, robotics etc. It involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.).

One of the main benefits of speech recognition system is that it lets user do other works simultaneously. The user can concentrate on observation and manual operations, and still control …show more content…

GOAL
11. CONCLUSION
12. BIBLIOGRAPHY

Artificial Intelligence For Speech Recognition

Introduction:

Artificial intelligence involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.).

AI is behavior of a machine, which, if performed by a human being, would be called intelligent. It makes machines smarter and more useful, and is less expensive than natural intelligence.

Natural language processing (NLP) refers to artificial intelligence methods of communicating with a computer in a natural language like English. The main objective of a NLP program is to understand input and initiate action.

Definition:

It is the science and engineering of making intelligent machines, especially intelligent computer programs.

AI means Artificial Intelligence. Intelligence” however cannot be defined but AI can be described as branch of computer science dealing with the simulation of machine exhibiting intelligent behavior.

History: Work started soon after …show more content…

As for the regression coefficients, typically the first and second order coefficients are extracted at every frame period to represent the spectral dynamics.

These coefficients are derivatives of the time function of the spectral coefficients and are called the delta and delta-delta-spectral coefficients respectively.

Speech Recognition:

The user communicates with the application through the appropriate input device i.e. a microphone. The Recognizer converts the analog signal into digital signal for the speech processing. A stream of text is generated after the processing. This source-language text becomes input to the Translation Engine, which converts it to the target language text.

Salient Features:
 Input Modes
 Through Speech Engine
 Through soft copy
 Interactive Graphical User Interface
 Format Retention
 Fast and standard translation
 Interactive Preprocessing tool
 Spell

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