Communications & Multimedia Signal Processing Refinement in FTLP-HNM system for Speech Enhancement Qin Yan Communication & Multimedia Signal Processing.

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Communications & Multimedia Signal Processing Refinement in FTLP-HNM system for Speech Enhancement Qin Yan Communication & Multimedia Signal Processing Group School of Engineering and Design, Brunel University 23 Nov, 2005

Communications & Multimedia Signal Processing Outline Review of FTLP-HNM system; Parameters estimation of HNM (incl. pitch/harmonic tracking in noise) Objective results of pitch, harmonic tracking and FTLP-HNM system Demo of enhanced speeches from old archive recordings

Communications & Multimedia Signal Processing Overview of FTLP-HNM Speech Enhancement System

Communications & Multimedia Signal Processing In HNM, speech is decomposed to two parts : Harmonic part and noise part. where L(t) denotes the number of harmonic included in the harmonic part, ω 0 denotes the pitch frequency. Harmonic : Noise : Synthesized Speech : where h the a time-varying autoregressive(AR) model and b is white Gaussian noise. Harmonic plus Noise Model

Communications & Multimedia Signal Processing HNM - Pitch Tracking In noisy condition the error function is modified to including SNR dependent weights The weighting function W(l) is a SNR-dependent given by Error function in frequency domain NOTE: The input speech frame is bandpassed to eliminated the parts which don’t contain explicit harmonics. For Each speech frame, it outputs several pitch candidates (N=3) and Viterbi algorithm then generates the final pitch tracks. It might be useful to have candidates from this method and traditional autocorrelation method.

Communications & Multimedia Signal Processing Figure - Comparison of the performance of different pitch track methods for speech in (a) train noise (b) car noise from 0dB SNR to clean. Results of Pitch Tracking

Communications & Multimedia Signal Processing HNM - Harmonic Tracking Peak picking Pitch Tracking Noise Speech VAD Noise model FFT Harmonic Frequency bin tracks Harmonic Track Candidates Smoothed Harmonic Magnitude by Kalman filter Tracking Data structure of harmonic track candidates are improved and speed up the whole system.

Communications & Multimedia Signal Processing Results of Harmonic Tracking in Clean Speech Figure - An illustration of pitch tracks of a speech segment at sampling frequency of 8kHz.

Communications & Multimedia Signal Processing Results of Harmonic Tracking in Noisy Speech Pitch recovery Harmonic Recovery

Communications & Multimedia Signal Processing Synthesis of Excitation by HNM Voiced Excitation : Unvoiced Excitation : Where b(m) is unit white Gaussian noise, e(m) is original excitation and a is the phases of original excitation.

Communications & Multimedia Signal Processing Results of Speech Enhancement Figure - Comparison of the harmonicity of MMSE and FTLP-HNM systems on train noisy speech at different SNRs Figure - Performance of MMSE and FTLP-HNM on train noisy speech at different SNR levels. Enhanced speech is synthesized by inverse filtering the HNM residual with cleaned LP shape.

Communications & Multimedia Signal Processing Original speech Enhanced speech Demo (1) Persian speech for Iranian King Mozaffareddin Shah

Communications & Multimedia Signal Processing Demo (2) Florence Nightinggale 1890 Original speechEnhanced speech

Communications & Multimedia Signal Processing