Impact of Technology in Filter Design for Noise Removal from Pathological Noisy Speech Signal & its Preprocessing
Syed Mohammad Ali1 and Pradeep Tulshiram Karule2
1. Department of Electronics & Telecommunication Engineering, Anjuman College of Engineering & Technology, Nagpur, India
2. Department of Electronics Engineering, Yeshwantrao chavan College of Engineering, Wanadongri, Nagpur, India
2. Department of Electronics Engineering, Yeshwantrao chavan College of Engineering, Wanadongri, Nagpur, India
Abstract—In the recent year the trend towards automated analysis of pathological noise signal has gain momentum. The awkwardness of analog equipment has simulated development of digital computer techniques for processing and analysis of pathological speech signal in patient care system. The above filter design techniques & prepossessing of speech signal can be used in any speech processing application.
This paper discusses pathological speech signal of patients and their preprocessing. In prepossessing, Speech signal is passed through Moving Average (M.A) filter1, High pass (H.P) filter for removal of noise. The output of filter is framed & these frames are passed through window. Typically, hamming window is used. This preprocessed output can be used for pathological voice recognition, speech identification, speaker identification & many more application.
Index Terms—Speech signal, moving average filter, highpass filter, framing, windowing
Cite: Syed Mohammad Ali and Pradeep Tulshiram Karule, "Impact of Technology in Filter Design for Noise Removal from Pathological Noisy Speech Signal & its Preprocessing," International Journal of Signal Processing Systems, Vol. 1, No. 1, pp. 39-42, June 2013.doi: 10.12720/ijsps.1.1.39-42
This paper discusses pathological speech signal of patients and their preprocessing. In prepossessing, Speech signal is passed through Moving Average (M.A) filter1, High pass (H.P) filter for removal of noise. The output of filter is framed & these frames are passed through window. Typically, hamming window is used. This preprocessed output can be used for pathological voice recognition, speech identification, speaker identification & many more application.
Index Terms—Speech signal, moving average filter, highpass filter, framing, windowing
Cite: Syed Mohammad Ali and Pradeep Tulshiram Karule, "Impact of Technology in Filter Design for Noise Removal from Pathological Noisy Speech Signal & its Preprocessing," International Journal of Signal Processing Systems, Vol. 1, No. 1, pp. 39-42, June 2013.doi: 10.12720/ijsps.1.1.39-42