9 citations · 17 across the 10 of their papers we have counts for
10 papers
CUHK-EE Systems for the vTAD Challenge at NCMMSC 2025
Aemon Yat Fei Chiu, Jingyu Li, Yusheng Tian +2
This paper presents the Voice Timbre Attribute Detection (vTAD) systems developed by the Digital Signal Processing & Speech Technology Laboratory (DSP&STL) of the Department of Ele…
Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech
Guangyan Zhang, Thomas Merritt, Manuel Sam Ribeiro +10
Neural text-to-speech systems are often optimized on L1/L2 losses, which make strong assumptions about the distributions of the target data space. Aiming to improve those assumptio…
Creating Personalized Synthetic Voices from Post-Glossectomy Speech with Guided Diffusion Models
Yusheng Tian, Guangyan Zhang, Tan Lee
This paper is about developing personalized speech synthesis systems with recordings of mildly impaired speech. In particular, we consider consonant and vowel alterations resulted…
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre
Guangyan Zhang, Ying Qin, Wenjie Zhang +5
The capability of generating speech with specific type of emotion is desired for many applications of human-computer interaction. Cross-speaker emotion transfer is a common approac…
Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech
Guangyan Zhang, Kaitao Song, Xu Tan +8
Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-b…
A study on the efficacy of model pre-training in developing neural text-to-speech system
Guangyan Zhang, Yichong Leng, Daxin Tan +5
In the development of neural text-to-speech systems, model pre-training with a large amount of non-target speakers' data is a common approach. However, in terms of ultimately achie…
Environment Aware Text-to-Speech Synthesis
Daxin Tan, Guangyan Zhang, Tan Lee
This study aims at designing an environment-aware text-to-speech (TTS) system that can generate speech to suit specific acoustic environments. It is also motivated by the desire to…
Applying the Information Bottleneck Principle to Prosodic Representation Learning
Guangyan Zhang, Ying Qin, Daxin Tan +1
This paper describes a novel design of a neural network-based speech generation model for learning prosodic representation.The problem of representation learning is formulated acco…
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style
Yuzi Yan, Xu Tan, Bohan Li +6
While recent text to speech (TTS) models perform very well in synthesizing reading-style (e.g., audiobook) speech, it is still challenging to synthesize spontaneous-style speech (e…
CUHK-EE Voice Cloning System for ICASSP 2021 M2VoC Challenge
Daxin Tan, Hingpang Huang, Guangyan Zhang +1
This paper presents the CUHK-EE voice cloning system for ICASSP 2021 M2VoC challenge. The challenge provides two Mandarin speech corpora: the AIShell-3 corpus of 218 speakers with…