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Prosody Detection from Text Using Aggregative Linguistic Features
Published in Springer Singapore
2018
Volume: 827
   
Pages: 736 - 749
Abstract
With the advent of digital revolution and new technologies the demand for commodious interfaces has increased. A speech interface in a person’s native/first language gives an epitome of ease in accessing information. Tamil Text-To-Speech synthesis is one such speech interface and this paper is focused on developing a prosody prediction model for enhancing the naturalness of the synthesized speech. The proposed prosody prediction model for multifarious Tamil text is developed to classify the text into three classes of high, mid and low using the generated aggregative linguistic feature score. The proposed prosody prediction model resulted in a f-measure of 0.84 when tested against multifarious text and the performance of this model is certainly encouraging to explore further in this direction. © Springer Nature Singapore Pte Ltd. 2018.
About the journal
JournalData powered by TypesetCommunications in Computer and Information Science Smart and Innovative Trends in Next Generation Computing Technologies
PublisherData powered by TypesetSpringer Singapore
ISSN1865-0929
Open Access0