A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

Ọdẹ´túnjí A. Odé´jọbí, Shun Ha Sylvia Wong, Anthony J. Beaumont

Research output: Contribution to journalArticle

Abstract

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications.
Original languageEnglish
Pages (from-to)325-349
Number of pages25
JournalComputer Speech and Language
Volume21
Issue number2
Early online date10 Jun 2006
DOIs
Publication statusPublished - Apr 2007

Keywords

  • decision theory
  • fuzzy sets
  • least squares approximations
  • mathematical models
  • measurement errors
  • regression analysis
  • speech synthesis

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