Improved Speaker Identification Using Fir-1 Based Filtering

This paper focuses on providing better performance in speaker identification technique by integrating FIR1 filter with audio recognition techniques. Main objective is to recognize speakers with wave transformation to attain improved outcomes. Speaker identification is becoming popular in real time security systems to enhance the person recognition i.e. it can find unauthorized persons easily. The approaches established so far are functioning accurately and providing decent outcomes but they are not much accurate in case of the noisy signals. This paper deals with efficiently identify speakers by using signal transposition and also gives enhanced outcomes than methods using neural networks. To attain this, a new hybrid methodology is proposed which will identify the speaker. The result of proposed algorithm is also compared with some well-known audio recognition algorithm and it is found that the proposed algorithm provide better results.