Speech is the fundamental mode of human communication, and its synthesis has long been
a core priority in human–computer interaction research. In recent years, machines have …

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 …

Speech emotion conversion is the task of modifying the perceived emotion of a speech
utterance while preserving the lexical content and speaker identity. In this study, we cast the …

Emotional voice conversion (EVC) seeks to convert the emotional state of an utterance while
preserving the linguistic content and speaker identity. In EVC, emotions are usually treated …

Emotional voice conversion (EVC) focuses on converting a speech utterance from a source
to a target emotion; it can thus be a key enabling technology for human-computer interaction …

Data augmentation is a widely used strategy for training robust machine learning models. It
partially alleviates the problem of limited data for tasks like speech emotion recognition …

As emotions play a central role in human communication, automatic emotion recognition has
attracted increasing attention in the last two decades. While multimodal systems enjoy high …

Emotional voice conversion (EVC) aims to change the emotional state of an utterance while
preserving the linguistic content and speaker identity. In this paper, we propose a novel 2 …

In this paper, we explored how to boost speech emotion recognition (SER) with the state-of-
the-art speech pre-trained model (PTM), data2vec, text generation technique, GPT-4, and …

This paper introduces a novel voice conversion (VC) model, guided by text instructions such
as “articulate slowly with a deep tone “or “speak in a cheerful boyish voice”. Unlike …