The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

In this study, we present recent developments on ESPnet: End-to-End Speech Processing
toolkit, which mainly involves a recently proposed architecture called Conformer …

Large-scale generative models such as GPT and DALL-E have revolutionized the research
community. These models not only generate high fidelity outputs, but are also generalists …

Abstract Language models have been successfully used to model natural signals, such as
images, speech, and music. A key component of these models is a high quality neural …

We introduce SPEAR-TTS, a multi-speaker text-to-speech (TTS) system that can be trained
with minimal supervision. By combining two types of discrete speech representations, we …

Large language models (LLMs) have exhibited remarkable capabilities across a variety of
domains and tasks, challenging our understanding of learning and cognition. Despite the …

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 …

Several recent end-to-end text-to-speech (TTS) models enabling single-stage training and
parallel sampling have been proposed, but their sample quality does not match that of two …

Scaling text-to-speech (TTS) to large-scale, multi-speaker, and in-the-wild datasets is
important to capture the diversity in human speech such as speaker identities, prosodies …

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 …