Modelling prosody in the task of human speech synthesis with the use of machine learning
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Date
2020
Authors
Процик, Олексій
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Abstract
Generating high fidelity speech using a text-to-speech (TTS) system remains a challenging task despite the decades of research and investigations. Modern TTS systems are very complex. For example, it is a common practice for a statistical TTS system to have a linguistic extractor in the front, which extracts different linguistic features. It is followed by a duration model to estimate the speech length in time of a given text and an acoustic feature prediction model. Given these features, it is all fed into a vocoder, which synthesizes speech out of acoustic features. All these components are trained independently and require extensive field knowledge to be sophisticated enough and produce considerable results. Because it has a modular design, it is prone to errors which will proceed in the following modules and can accumulate.
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Keywords
modelling prosody, the task of human speech, synthesis, the use, machine learning, бакалаврська робота