Bonfring International Journal of Research in Communication Engineering, Vol. 6, Special Issue, November 2016 48 Abstract--- Artificial intelligence involves studying the thought processes of human beings and also representing those processes via computers and robots like man made machines. Speech recognition system lets user do other works simultaneously so that the user can concentrate on observation and manual operations. With the help of speaker recognition technology we can help physically challenged skilled persons. So that they can do their works without the help of others. This Artificial Speech Recognition technology is also used in various applications. Now days this technology is also used by CID officers in order to trap the criminal activities.This technology is also used in military applications. Keywords--- NLP, LPC, DFT, MMSE Technique. I. INTRODUCTION RTIFICIAL intelligence involves two basically deals with studying the thought processes of human beings and then representing those processes via computer[1]. There is one artificial intelligence method through which we can communicate with a computer in a natural language like English which is termed as Natural Language Processing(NLP). The main objective of a NLP program is to understand the applied input and then initiate related action. II. DEFINITION Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs so that it can serve most of user needs[2].AI implies Artificial Intelligence. Intelligence is the factor which cannot be defined but whereas AI can be defined as branch of computer science which deals with the simulation of machine that exhibits intelligent behavior as the human being. Speech recognition is considered to be one of the applications of the artificial intelligence which mainly deals with the translation of user spoken words into the corresponding text. III. OBJECTIVES 1) Deals with understanding human thinking capabilities: This means to obtain deep knowledge of human memory, Problem solving ability, learning and decision making etc. S.V. Viraktamath. Chaitra Prakash Shet, Student, Department of Electronics & Communication, Shri Dharmasthala Manjunatheshwara College of Engineering and Technology, India. E-mail:chaitraprakashshet@gmail.com Pooja Ravindra Nayak, Student, Department of Electronics & Communication, Shri Dharmasthala Manjunatheshwara College of Engineering and Technology, India. E-mail:poojaravindranayak@gmail.com DOI:10.9756/BIJRCE.8199 2) Replaces human in intelligent tasks: Results in building of system in order to help humans think better, faster and deeper. 3) Enhance human intelligence: It implies building program to exceed human intelligence. 4) Deals with Coherent discourse: Communication with people using natural language involves intelligent dialogue. IV. SPEAKER INDEPENDENCY Usually the speech quality varies from one person to another person. So it becomes difficult to design an electronic machine that recognizes everyone’s voice. The system is made simpler and also more reliable by designing it in order to recognize single person’s voice. The computer is trained to the voice of the particular individual. Such developed system is called speaker-dependent system. Speaker independent systems can be used by anybody, as it recognizes any voice, although the characteristics vary widely from one speaker to another. These speaker independent systems are costly and complex to construct. These systems have got limited vocabularies. There are some factors that may affect the quality of speech recognition. That includes grammar used by the speaker and accepted by the system, noise level, noise type, position of the microphone, and speed and manner of the user’s speech and so on. V. ENVIRONMENTAL IMPACT The recognition rate usually drops widely when a system is trained and tested under different conditions. It is necessary that we should be aware of the variations present when different microphones are used in training, testing, and also during development of required procedures. Such that with this the accuracy of recognition systems can be improved to greater extent. Accuracy of recognition systems are going to be degraded mainly because of Acoustical distortions. Obstacles for robustness include additive noise from machinery, competing talkers, reverberation from surface reflections in a room, and spectral shaping by microphones and also the vocal tracts of individual speakers and so on. The sources of distortions are categorized as additive noise and distortions resulting from the convolution of the speech signal with an unknown linear system. There are various algorithms proposed for speech enhancement. They are given as follows: 1. Spectral subtraction of the obtained DFT coefficients. 2. The DFT coefficients of corrupted speech are estimated by applying MMSE technique Convoluted S.V. Viraktamath, Chaitra P. Shet and Pooja R. Nayak Artificial Intelligence and its Application in Speech Recognition A ISSN 2277 - 5080 | © 2016 Bonfring