Expanding the language coverage of speech technology has the potential to improve
access to information for many more people. However, current speech technology is …

YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker
TTS. Our method builds upon the VITS model and adds several novel modifications for zero …

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 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 …

Code-Switching, a common phenomenon in written text and conversation, has been studied
over decades by the natural language processing (NLP) research community. Initially, code …

In this paper, we present SANE-TTS, a stable and natural end-to-end multilingual TTS
model. By the difficulty of obtaining multilingual corpus for given speaker, training …

We provide a systematic review of past studies that use multilingual data for text-to-speech
(TTS) of low-resource languages (LRLs). We focus on the strategies used by these studies …

In this paper, we propose a method to learn unified representations of multilingual speech
and text with a single model, especially focusing on the purpose of speech synthesis. We …

Neural text-to-speech (TTS) has achieved humanlike synthetic speech for single-speaker,
single-language synthesis. Multilingual TTS systems are limited to resource-rich languages …

In the articulatory synthesis task, speech is synthesized from input features containing
information about the physical behavior of the human vocal tract. This task provides a …