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The current state of the art TTS synthesis can produce synthesized speech with highly decent quality if rich segmental and suprasegmental information are given. However, some suprasegmental features, e.g., Tone and Break (TOBI), are time consuming due to being manually labeled with a high inconsistency among different annotators. In this paper, we investigate the use of word embedding, which represents...
Deep Neural Network (DNN), which can model a long-span, intricate transform compactly with a deep-layered structure, has recently been investigated for parametric TTS synthesis with a fairly large corpus (33,000 utterances) [6]. In this paper, we examine DNN TTS synthesis with a moderate size corpus of 5 hours, which is more commonly used for parametric TTS training. DNN is used to map input text...
In this study, we investigate the break index labeling problem with a syntactic-to-prosodic structure conversion. The statistical relationship between the mapped syntactic tree structure and prosodic tree structure of sentences in the training set is used to generate a Synchronous Tree Substitution Grammar (STSG) which can describe the probabilistic mapping (substitution) rules between them. For a...
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