Speech processing for makhraj recognition

In our daily day, improvement of makhraj for Arabic alphabets is a topic that very useful in many applications and environments. The existing system cannot recognize the appropriate pronunciation of each alphabet with the existence of noise. As an example “ha”, with the disturbance from the noise, the system may recognize wrong alphabet like “kho”. This paper focus on noise removal in makhraj recognition using Least Mean Square (LMS) Algorithm based on Adaptive Filter to search for the optimal solution to adaptive filter, including system identification and noise cancellation. There are 30 Arabic alphabets from until. However, this project will only use 7 alphabets as samples that are from until. The speech processing will be used to obtain same waveform output from two different situations. The filtered data will be processed to match the standard pronunciations and it will be integrated with filter design process in MATLAB. As a result, the waveform of noise cancellation using LMS algorithm is quite similar with the waveform of reference signal. As a conclusion, it is proved that noise cancellation method remove noise from unknown system.