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 …

The mainstream neural text-to-speech (TTS) pipeline is a cascade system, including an
acoustic model (AM) that predicts acoustic feature from the input transcript and a vocoder …

Accented text-to-speech (TTS) synthesis seeks to generate speech with an accent (L2) as a
variant of the standard version (L1), which is challenging as L2 is different from L1 in terms …

Although current neural text-to-speech (TTS) models are able to generate high-quality
speech, intensity controllable emotional TTS is still a challenging task. Most existing …

Audio language models have recently emerged as a promising approach for various audio
generation tasks, relying on audio tokenizers to encode waveforms into sequences of …

We propose PromptTTS++, a prompt-based text-to-speech (TTS) synthesis system that
allows control over speaker identity using natural language descriptions. To control speaker …

Expressive text-to-speech systems have undergone significant advancements owing to
prosody modeling, but conventional methods can still be improved. Traditional approaches …

In this paper, we present ControlSpeech, a text-to-speech (TTS) system capable of fully
cloning the speaker's voice and enabling arbitrary control and adjustment of speaking style …

Achieving high fidelity and speaker similarity in text-to-speech speaker adaptation with
limited amount of data is a challenging task. Most existing methods only consider adapting …

We propose an end-to-end empathetic dialogue speech synthesis (DSS) model that
considers both the linguistic and prosodic contexts of dialogue history. Empathy is the active …