dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Bloothooft, G. | |
dc.contributor.advisor | Binnenpoorte, D. | |
dc.contributor.author | Versteegh, B. | |
dc.date.accessioned | 2012-09-06T17:03:17Z | |
dc.date.available | 2012-09-06 | |
dc.date.available | 2012-09-06T17:03:17Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/20733 | |
dc.description.abstract | Current Text-to-Speech software such as Vocalizer is able to produce fairly natural speech from texts that do not contain meta-text. Meta-text that is part of most modern electronic text-formats is ignored by Vocalizer, resulting in unnatural output, or loss of structural information. The present research designs and tests a method to preserve meta-text information in Text-to-Speech conversion. Preservation was done by mapping various structural elements in the e-text to speech, non-speech audio and pauses. A listening experiment, using 23 participants, was performed to measure this method's effectiveness in improving three aspects: listening comfort; perceived speech intelligibility and perceived synthesis quality. In the case of list-structures, significant improvements between 18% and 30% were measured in all three aspects. Omission of a large data-table resulted in significant improvements between 21% and 61% in all three aspects as well. Mappings for headings, images, page-breaks did not result in significant improvements. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 217348 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.title | Using meta-text to improve intelligibility of speech-synthesized e-texts | |
dc.type.content | Bachelor Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | text-to-speech, meta-text, markup, speech-synthesis, sound icons, vocalizer | |
dc.subject.courseuu | Kunstmatige Intelligentie | |