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 …

We introduce a novel speech synthesis system, called NAUTILUS, that can generate speech
with a target voice either from a text input or a reference utterance of an arbitrary source …

This paper presents the sequence-to-sequence (seq2seq) baseline system for the voice
conversion challenge (VCC) 2020. We consider a naive approach for voice conversion (VC) …

Conventional text-to-speech (TTS) research has predominantly focused on enhancing the
quality of synthesized speech for speakers in the training dataset. The challenge of …

This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS
quality with lower supervised data requirements via Vector-Quantized Self-Supervised …

We present a cross-lingual speaker adaptation method based on domain adaptation and a
speaker consistency loss for text-tospeech (TTS) synthesis. Existing monolingual speaker …

Neural Text-to-speech (TTS) synthesis is a powerful technology that can generate speech
using neural networks. One of the most remarkable features of TTS synthesis is its capability …

In voice conversion (VC), an approach showing promising results in the latest voice
conversion challenge (VCC) 2020 is to first use an automatic speech recognition (ASR) …

Few-shot speaker adaptation is a specific Text-to-Speech (TTS) system that aims to
reproduce a novel speaker's voice with a few training data. While numerous attempts have …

Building multispeaker neural network-based text-to-speech synthesis systems commonly
relies on the availability of large amounts of high quality recordings from each speaker and …