Speech technologies have been developed for decades as a typical signal processing area,
while the last decade has brought a huge progress based on new machine learning …

Emotion embedding space learned from references is a straight-forward approach for
emotion transfer in encoder-decoder structured emotional text to speech (TTS) systems …

The cross-speaker emotion transfer task in text-to-speech (TTS) synthesis particularly aims
to synthesize speech for a target speaker with the emotion transferred from reference …

Cross-speaker emotion transfer is a common approach to generating emotional speech
when speech data with emotion labels from target speakers is not available. This paper …

Recently, attention-based end-to-end speech synthesis has achieved superior performance
compared to traditional speech synthesis models, and several approaches like global style …

In this paper, we investigate multi-speaker emotional acoustic modeling methods for
convolutional neural network (CNN) based speech synthesis system. For emotion modeling …

This paper proposes a hierarchical generative model with a multi-grained latent variable to
synthesize expressive speech. In recent years, fine-grained latent variables are introduced …

This paper proposes architectures that facilitate the extrapolation of emotional expressions
in deep neural network (DNN)-based text-to-speech (TTS). In this study, the meaning of …

Affective computing is an emerging interdisciplinary field where computational systems are
developed to analyze, recognize, and influence the affective states of a human. It can …

The aim of multi-speaker emotional speech synthesis is to generate speech for a designated
speaker in a desired emotional state. The task is challenging due to the presence of speech …