Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural
speech given text, is a hot research topic in speech, language, and machine learning …

In this paper, we present AISHELL-3, a large-scale and high-fidelity multi-speaker Mandarin
speech corpus which could be used to train multi-speaker Text-to-Speech (TTS) systems …

This paper introduces Opencpop, a publicly available high-quality Mandarin singing corpus
designed for singing voice synthesis (SVS). The corpus consists of 100 popular Mandarin …

The Cocktail party problem, which is tracing and identifying a specific speaker's speech
while numerous speakers communicate concurrently is one of the crucial problems still to be …

Background noise and room reverberation are regarded as two major factors to degrade the
subjective speech quality. In this paper, we propose an integrated framework to address …

Zero-shot text-to-speech aims at synthesizing voices with unseen speech prompts. Previous
large-scale multispeaker TTS models have successfully achieved this goal with an enrolled …

The primary aim of this study was to contribute to the development of multilingual automatic
speech recognition for lower-resourced Turkic languages. Ten languages—Azerbaijani …

Unifying acoustic and linguistic representation learning has become increasingly crucial to
transfer the knowledge learned on the abundance of high-resource language data for low …

Recently, there has been an increasing interest in neural speech synthesis. While the deep
neural network achieves the state-of-the-art result in text-to-speech (TTS) tasks, how to …

Recently, text-guided content generation has received extensive attention. In this work, we
explore the possibility of text description-based speaker generation, ie, using text prompts to …