A speaker extraction algorithm seeks to extract the speech of a target speaker from a multi-
talker speech mixture when given a cue that represents the target speaker, such as a pre …

Emotional text-to-speech synthesis (ETTS) has seen much progress in recent years.
However, the generated voice is often not perceptually identifiable by its intended emotion …

Cross-lingual personalized speech generation seeks to synthesize a target speaker's voice
from only a few training samples that are in a different language. One popular technique is to …

Speech separation seeks to separate individual speech signals from a speech mixture.
Typically, most separation models are trained on synthetic data due to the unavailability of …

Cross-lingual voice conversion (XVC) transforms the speaker identity of a source speaker to
that of a target speaker who speaks a different language. Due to the intrinsic differences …

Feature extractionplays an important role before pattern recognition takes place. The
existing artificial neural networks (ANNs), however, ignoreto learn and represent temporal …

Audio-visual speech synthesis (AVSS) has garnered attention in recent years for its utility in
the realm of audio-visual learning. AVSS transforms one speaker's speech into another's …

Abstract Cross-Lingual Voice Conversion (XVC) aims to modify a source speaker identity
towards a target while preserving the source linguistic content. This paper introduces a cycle …

Automatic speech quality assessment aims to train a model capable of automatically
measuring the performance of synthesis systems. This is a challenging task, especially …

Voice conversion aims to change the timber of the source speaker to that of the target
speaker without changing the speech content. The cross-lingual voice conversion requires …