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Fuming Fang

4 accepted papers

2020

Zero-Shot Multi-Speaker Text-To-Speech with State-Of-The-Art Neural Speaker Embeddings

ICASSP 2020accepted

While speaker adaptation for end-to-end speech synthesis using speaker embeddings can produce good speaker similarity for speakers seen during training, there remains a gap for zero-shot adaptation to unseen speakers. We investigate multi-speaker modeling for end-to-end text-to-speech synthesis and…

Cited by 0SourceScholar
2019

Audiovisual Speaker Conversion: Jointly and Simultaneously Transforming Facial Expression and Acoustic Characteristics

ICASSP 2019accepted

An audiovisual speaker conversion method is presented for simultaneously transforming the facial expressions and voice of a source speaker into those of a target speaker. Transforming the facial and acoustic features together makes it possible for the converted voice and facial expressions to be hig…

Cited by 0SourceScholar
2018

High-Quality Nonparallel Voice Conversion Based on Cycle-Consistent Adversarial Network

ICASSP 2018accepted

Although voice conversion (VC) algorithms have achieved remarkable success along with the development of machine learning, superior performance is still difficult to achieve when using nonparallel data. In this paper, we propose using a cycle-consistent adversarial network (CycleGAN) for nonparallel…

Cited by 0SourceScholar
2016

Noise robust speech recognition using recent developments in neural networks for computer vision

ICASSP 2016accepted

Convolutional Neural Networks (CNNs) are superior to fully connected neural networks in various speech recognition tasks and the advantage is pronounced in noisy environments. In recent years, many techniques have been proposed in the computer vision community to improve CNN's classification perform…

Cited by 0SourceScholar