Speech synthesis, also known as text-to-speech (TTS), has attracted increasingly more
attention. Recent advances on speech synthesis are overwhelmingly contributed by deep …

End-to-end text-to-speech (TTS) has shown great success on large quantities of paired text
plus speech data. However, laborious data collection remains difficult for at least 95% of the …

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 …

Building text-to-speech (TTS) systems requires large amounts of high quality speech
recordings and annotations, which is a challenge to collect especially considering the …

This paper presents an accented text-to-speech (TTS) synthesis framework with limited
training data. We study two aspects concerning accent rendering: phonetic (phoneme …

Recently, sequence-to-sequence models with attention have been successfully applied in
Text-to-speech (TTS). These models can generate near-human speech with a large …

Building end-to-end speech synthesisers for Indian languages is challenging, given the lack
of adequate clean training data and multiple grapheme representations across languages …

The low similarity and naturalness of synthesized speech remain a challenging problem for
speaker adaptation with few resources. Since the acoustic model is too complex to interpret …

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model
training problematic for most existing languages, including languages that do not even have …

The paper describes the CASIA speech synthesis system entry for challenge M2VoC 2021.
The low similarity and naturalness of synthesized speech remains a challenging problem for …