Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) SINGLE CHANNEL SPEECH ENHANCEMENT TECHNIQUE FOR LOW SNR QUASI-PERIODIC.

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Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) SINGLE CHANNEL SPEECH ENHANCEMENT TECHNIQUE FOR LOW SNR QUASI-PERIODIC NOISE BASED ON REDUCED ORDER LINEAR PREDICTION Chandan K A Reddy, Vahid Montazeri, Yu Rao, Issa M S Panahi

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) Outline of the presentation Introduction- Problem statement and our contribution Modeling of Quasi-Periodic Signal Proposed Method Experimental Results and Performance Evaluation Evaluation Metrics Performance Evaluation of the Proposed Method Conclusion 2

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) Introduction: Quasi Periodic nature of the noise can be exploited in the Speech Enhancement algorithms. Noise generated using a Functional Magnetic Resonance Imaging (fMRI) is Quasi Periodic in nature. The speech response of the patient is generally recorded for post analysis. Hence it is necessary to suppress the background fMRI acoustic noise. 3

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) 4 Distance between the peaks is 792 samples Fig 1. Overlap of 3 subsequent slices and Normalized Autocorrelation of fMRI noise from a 3-Tesla (30 slices/ 2sec) machine sampled at 16 kHz

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) 5 Fig 2. Mean Square Error vs Filter Order [1] G. Kannan, A.A Milani, I.M.S. Panahi and R.W. Briggs, “An Efficient Feedback Active noise control algorithm based on reduced-order linear predictive modelling of fMRI acoustic noise”. IEEE Trans. Biomed. Eng., vol. 58, no. 12, pp , Dec 2011.

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) 6 Fig 3. Block diagram of the proposed method

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Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) Performance Evaluation: 13 Fig 4. Time domain plots of the noisy speech (left) and the enhanced speech (right) at SNR = -5 dB. X-axis is the time (in sec) and Y-axis is the normalized amplitude. LogMMSEReduced LP+LogMMSE Noisy Speech

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) 14 Fig 5. Quantitative measures of Quality and Intelligibility

Statistical Signal Processing Research Laboratory(SSPRL) UT Acoustic Laboratory(UTAL) Thanks you. For your time and patience 15