26 citations · 107 across the 24 of their papers we have counts for
5 papers · 1 filter
Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset
Kun Zhou, Berrak Sisman, Rui Liu +1
Emotional voice conversion aims to transform emotional prosody in speech while preserving the linguistic content and speaker identity. Prior studies show that it is possible to dis…
GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis
Rui Liu, Berrak Sisman, Haizhou Li
Attention-based end-to-end text-to-speech synthesis (TTS) is superior to conventional statistical methods in many ways. Transformer-based TTS is one of such successful implementati…
Modeling Prosodic Phrasing with Multi-Task Learning in Tacotron-based TTS
Rui Liu, Berrak Sisman, Feilong Bao +2
Tacotron-based end-to-end speech synthesis has shown remarkable voice quality. However, the rendering of prosody in the synthesized speech remains to be improved, especially for lo…
Expressive TTS Training with Frame and Style Reconstruction Loss
Rui Liu, Berrak Sisman, Guanglai Gao +1
We propose a novel training strategy for Tacotron-based text-to-speech (TTS) system to improve the expressiveness of speech. One of the key challenges in prosody modeling is the la…
WaveTTS: Tacotron-based TTS with Joint Time-Frequency Domain Loss
Rui Liu, Berrak Sisman, Feilong Bao +2
Tacotron-based text-to-speech (TTS) systems directly synthesize speech from text input. Such frameworks typically consist of a feature prediction network that maps character sequen…