Speech processing phd thesis

In addition, the proposed approach is improved by replacing the log with the generalised logarithmic function in the Hilbert transform and also by computing the group delay via regression filter.

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In contrast to the magnitude spectrum whose fine and coarse structures have a clear relation to speech perception, the phase spectrum is difficult to interpret and manipulate. In noise, some subjects benefited with the 6-of-8 strategy. This thesis investigates the affect of colored noise viz.

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The problems it presents are analysed and discussed, some solutions are proposed and finally the corresponding formulae are derived. However, selective stimulation is not often, or at least imperfectly, achieved even with the most modern cochlear implant designs and speech processing strategies. Nonetheless, the speech phase spectrum has recently gained renewed attention. Little is known about the effect of noise on the spectrum of speech. August This thesis presents a new technique for subband feedback active noise control. In addition, patients with strong susceptibility to electrical-field interactions produced higher speech recognition scores for sequential than simultaneous speech strategies. The robustness gain achieved through using statistical normalisation and generalised logarithmic function encouraged the use of more advanced model-based statistical techniques such as vector Taylor Series VTS.

May This thesis addresses the problem of helping hearing-impaired people to use telephones. A simultaneous masking task was used to measure electrical-field interactions as a function of electrode separation for monopolar and bipolar configurations.

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Objective measures and informal listening tests showed that the proposed modified spectral subtraction method combined with perceptual weighting outperformed the conventional power spectral subtraction method resulting in better speech quality and reduced levels of musical noise.

August An understanding of how information about the speech signal is spread among the various frequency bands of the spectrum is essential in numerous communications, audio and hearing related applications.

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The subband processing is done using relatively short fixed FIR filters. Objective measures and informal listening tests showed that the proposed modified spectral subtraction method combined with perceptual weighting outperformed the conventional power spectral subtraction method resulting in better speech quality and reduced levels of musical noise. The present study addresses this question in a systematic fashion, considering all possible combinations of missing disjoint bands from the spectrum. We believe that this variability was due to the amount of channel interaction. This is done by a piecewise linear estimation based on line spectral frequencies, and a statistical speech-frame classification technique based on Hidden Markov Models integrated to overcome the drawback of conventional bandwidth extension algorithms. In this thesis, the Clarion research interface was used to evaluate the performance of commercially available as well as new speech processing strategies. This thesis proposes a modification to the conventional spectral subtraction approach in order to address the problem of musical noise and speech distortion that is inherent to the conventional spectral subtraction based approach. Using subband processing can considerably reduce the length of the adaptive filter. December The variability in patient performance noticed in cochlear implant users demands the development of new and improved speech processing strategies that will help improve speech recognition for poor users of the device. May This thesis addresses the problem of helping hearing-impaired people to use telephones. These strategies differed in the degree of simultaneity and rate of stimulation. Although many studies investigated the intelligibility of high-pass, low-pass and band-pass filtered speech, not many studies investigated the perception of band-stop filtered speech i.
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Theses in Speech Processing Lab at UT