Fourier transform is very well known technique which transforms time domain signal to frequency domain to get the frequency coefficients. Since, audio is very susceptible to noise hence it is required to extract specific frequency components. When the audio signal is received, the extraction of frequency response is extremely needed.
Between sender and receiver, signal is also being processed by using a lot of method. Everyday audio is being transmitted through transmission medium from source to destination. Speech signal is a very important parameter for communication. KeywordsĪudio, wavelet, FFT, IFFT, noise, feature extraction. The proposed wavelet method found to be more summarized over conventional FFT and Wavelet in finding the small abnormalities of audio signal.
In this paper, an improved wavelet method has been proposed to extract the precise detection of small abnormalities of both original and noise corrupted speech signal which are taken empirically by writing MATLAB program. So, it is needed to be extracted by signal processing method because there are not visible of graphical audio signal.
But it is difficult to extract the changes of small variation of speech signal with time-varying morphological characteristics. The features of Audio, especially speech signal may be extracted using FFT (Fast Fourier Transform) and Wavelet to detect the frequency information of the signal. Speech contains very important frequency information of human being. Speech recognition is also significant and very well known of audio processing. Speech is one of the vital signals of acoustic classification.