MixGAN-TTS: Efficient and Stable Speech Synthesis Based on Diffusion Model-Reference-Cited by-同舟云学术

MixGAN-TTS: Efficient and Stable Speech Synthesis Based on Diffusion Model

Author:

Deng Yan¹^ORCID,Wu Ning²^ORCID,Qiu Chengjun³^ORCID,Luo Yangyang¹^ORCID,Chen Yan¹^ORCID

Affiliation:

1. School of Computer, Electronics and Information, Guangxi University, Nanning, China

2. Key Laboratory of Beibu Gulf Offshore Engineering Equipment and Technology, Beibu Gulf University, Qinzhou, China

3. College of Mechanical Naval Architecture and Ocean Engineering, Beibu Gulf University, Qinzhou, China

Funder

China State Shipbuilding Corporation (CSSC) Guangxi Shipbuilding and Offshore Engineering Technology Collaboration Project

100 Scholar Plan of the Guangxi Zhuang Autonomous Region of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference33 articles.

1. Glow-TTS: A generative flow for text-to-speech via monotonic alignment search;kim;Proc Adv Neural Inf Process Syst,2020

2. FastSpeech 2: Fast and high-quality end-to-end text to speech;ren;arXiv 2006 04558,2020

3. DiffGAN-TTS: High-fidelity and efficient text-to-speech with denoising diffusion GANs;liu;arXiv 2201 11972,2022

4. PortaSpeech: Portable and high-quality generative text-to-speech;ren;Proc Adv Neural Inf Process Syst,2021

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