Brian Gabelman

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Vocal tremors characterize many pathological voices, but acoustic-perceptual aspects of tremor are poorly understood. To investigate this relationship, 2 tremor models were implemented in a custom voice synthesizer. The first modulated fundamental frequency (F0) with a sine wave. The second provided irregular modulation. Control parameters in both models(More)
Pathological voices are particularly difficult to inverse filter and fit with source models, in part, because of source-tract interactions inherent in these voice types. In order to obtain good synthetic copies of these voices, we need to know the practical importance of accurately inverse filtering and modeling individual voice sources. To this end, thirty(More)
FM and source noise characteristics of pathological voices are analyzed and modeled using precision interpolating pitch tracking. Detailed tracking data allows segregation of pitch variations into low frequency (tremor) and high frequency pitch variation (HFPV) time series. Tremor data is used to resample the original voice into a quasi-constant pitch(More)
To determine the perceptual importance of differences in noise characteristics, a sample of pathological voices was modeled using analysis by synthesis techniques. Spectral characteristics of noise were varied to create different synthetic versions of each voice sample. Expert listeners compared each synthetic stimulus to the original voice sample. The(More)
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