This thesis introduces a general method for incorporating the distributional analysis of textual and linguistic objects into text-to-speech (TTS) conversion systems. Conventional TTS conversion uses intermediate layers of representation to bridge the gap between text and speech. Collecting the annotated data needed to produce these intermediate layers is a far from a trivial task, possibly prohibitively so for languages in which no such resources are in existence. Distributional analysis, in contrast, proceeds in an unsupervised manner and so enables the creation of systems using textual data that are not annotated. The method, therefore, aids the building of systems for languages in which conventional linguistic resources are scarce but is not restricted to these languages.
The distributional analysis proposed here places the textual objects analyzed in a continuous-valued space, rather than specifying a hard categorization of those objects. This space is then partitioned during the training of acoustic models for synthesis, so that the models generalize over objects’ surface forms in a way that is acoustically relevant.
The method is applied to three levels of textual analysis: to the characterization of sub-syllabic units, word units, and utterances. The entire system was built with no reliance on manually labeled data or language-specific expertise. Results of a subjective evaluation are presented.
|Commitee:||Yang, Hengzhao, Yeh, Hen-Geul (Henry)|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 57/04M(E), Masters Abstracts International|
|Subjects:||Language, Artificial intelligence, Computer science|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be