Speech conversion and its application to alaryngeal speech enhancement.
| dc.contributor.author | Bi, Ning. | |
| dc.creator | Bi, Ning. | en_US |
| dc.date.accessioned | 2011-10-31T18:35:29Z | |
| dc.date.available | 2011-10-31T18:35:29Z | |
| dc.date.issued | 1995 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/187290 | |
| dc.description.abstract | In this investigation, a vector quantization (VQ)-based speech conversion algorithm and a linear multivariate regression (LMR)-based speech conversion algorithm were modified, and the modified algorithms were applied to the enhancement of alaryngeal speech. The modifications were aimed at reducing the spectral distortion (bandwidth increase) in the VQ-based system and the spectral discontinuity in the LMR-based system. The spectral distortion in the VQ-based algorithm was compensated by formant enhancement using chirp z-transform and cepstral weighting. The spectral discontinuity in the LMR-based system was minimized by the use of overlapped subsets during the constructing of conversion mapping function. These modified algorithms were evaluated using simulated data and speech samples. Results of the evaluations indicated that the modified algorithms reduced conversion distortions. These modified algorithms were also used for the enhancement of alaryngeal speech. Results of perceptual evaluation indicated that listeners generally preferred to listen to the enhanced speech samples. | |
| dc.language.iso | en | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.title | Speech conversion and its application to alaryngeal speech enhancement. | en_US |
| dc.type | text | en_US |
| dc.type | Dissertation-Reproduction (electronic) | en_US |
| dc.contributor.chair | Qi, Yingyong | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | doctoral | en_US |
| dc.contributor.committeemember | Glattke, Theodore J. | en_US |
| dc.contributor.committeemember | Shipp, Thomas | en_US |
| dc.identifier.proquest | 9604516 | en_US |
| thesis.degree.discipline | Speech and Hearing Sciences | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | Ph.D. | en_US |
| dc.description.note | This item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at repository@u.library.arizona.edu. | |
| dc.description.admin-note | Original file replaced with corrected file October 2023. | |
| refterms.dateFOA | 2018-06-18T13:33:15Z | |
| html.description.abstract | In this investigation, a vector quantization (VQ)-based speech conversion algorithm and a linear multivariate regression (LMR)-based speech conversion algorithm were modified, and the modified algorithms were applied to the enhancement of alaryngeal speech. The modifications were aimed at reducing the spectral distortion (bandwidth increase) in the VQ-based system and the spectral discontinuity in the LMR-based system. The spectral distortion in the VQ-based algorithm was compensated by formant enhancement using chirp z-transform and cepstral weighting. The spectral discontinuity in the LMR-based system was minimized by the use of overlapped subsets during the constructing of conversion mapping function. These modified algorithms were evaluated using simulated data and speech samples. Results of the evaluations indicated that the modified algorithms reduced conversion distortions. These modified algorithms were also used for the enhancement of alaryngeal speech. Results of perceptual evaluation indicated that listeners generally preferred to listen to the enhanced speech samples. |
