Single Frequency Filtering for Processing Degraded Speech

Abstract

This thesis proposes new signal processing methods to highlight some robust speech-specific features present in the degraded speech. It considers different types of degradations that occur in practice. The signal processing methods are based on single frequency filtering (SFF) of speech signal. The SFF output gives magnitude or envelope and the phase of the speech signal at any desired frequency with high frequency newlineresolution. The SFF output at each frequency gives some segments with high signal-to-noise ratio (SNR), as the noise power in the near zero bandwidth resonator of the single frequency will be very small, whereas the signal component, if it exists, will have high power. Thus the high SNR regions will be at different times for different frequencies. This property of the SFF analysis of speech is exploited for extracting newlinea few robust features from the degraded speech, irrespective of the type and extent of degradation newline newlineSome of the major contributions of this work newlineare the following: newline(a) A new signal processing method called single frequency filtering (SFF) method is proposed which gives high signal-to-noise newlineratio (SNR) regions in both time and frequency domains for speech affected with different types of degradations. newline(b) A new method for speech/nonspeech newlinedetection is proposed exploiting the high SNR features in the SFF outputs of degraded speech. The procedure works for all types of degradations, newlinewithout specifically tuning for any specific type of degradation. newline(c) The high SNR characteristic of the SFF output is also exploited for estimating newline the fundamental frequency by exploiting information at the frequency that gives the highest SNR for that segment.(d) The noise compensation technique newlineproposed for voice activity detection (VAD) is applied for extracting the location of the significant impulse-like excitation within a glottal cycle. newline