Machine Learning is an increasingly important technology dealing with the growing
complexity of the digitalised world. Despite the fact, that we live in a 'Big data'world where …

Nowadays speech synthesis or text to speech (TTS), an ability of system to produce human
like natural sounding voice from the written text, is gaining popularity in the field of speech …

In this paper, we first provide a review of the state-of-the-art emotional voice conversion
research, and the existing emotional speech databases. We then motivate the development …

Expressive text-to-speech (TTS) aims to synthesize speech with varying speaking styles to
better reflect human speech patterns. In this study, we attempt to use natural language as a …

Style transfer TTS has shown impressive performance in recent years. However, style
control is often restricted to systems built on expressive speech recordings with discrete style …

Emotional speech synthesis aims to synthesize human voices with various emotional effects.
The current studies are mostly focused on imitating an averaged style belonging to a specific …

Designing and generating new data under targeted properties has been attracting various
critical applications such as molecule design, image editing and speech synthesis …

Neural text-to-speech (TTS) approaches generally require a huge number of high quality
speech data, which makes it difficult to obtain such a dataset with extra emotion labels. In …

While recent neural text-to-speech (TTS) systems perform remarkably well, they typically
require a substantial amount of recordings from the target speaker reading in the desired …

Text-to-Speech (TTS) aims to convert the input text to a human-like voice. With the
development of deep learning, encoder-decoder based TTS models perform superior …