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20222026
most citedSeed-TTS: A Family of High-Quality Versatile Speech Generation Models

7 citations · 9 across the 13 of their papers we have counts for

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eess.AS2026

WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling

Wenxi Chen, Dongya Jia, Yushen Chen +11

Recently, diffusion models operating on VAE latents or mel-spectrograms have become the dominant paradigm for zero-shot TTS. Although these compressed representations improve gener…

eess.AS2025

DiSTAR: Diffusion over a Scalable Token Autoregressive Representation for Speech Generation

Yakun Song, Xiaobin Zhuang, Jiawei Chen +8

Recent attempts to interleave autoregressive (AR) sketchers with diffusion-based refiners over continuous speech representations have shown promise, but they remain brittle under d…

eess.AS2025

Direct Preference Optimization for Speech Autoregressive Diffusion Models

Zhijun Liu, Dongya Jia, Xiaoqiang Wang +4

Autoregressive diffusion models (ARDMs) have recently been applied to speech generation, achieving state-of-the-art (SOTA) performance in zero-shot text-to-speech. By autoregressiv…

eess.AS2025

AudioMorphix: Training-free audio editing with diffusion probabilistic models

Jinhua Liang, Yuanzhe Chen, Yi Yuan +5

Editing sound with precision is a crucial yet underexplored challenge in audio content creation. While existing works can manipulate sounds by text instructions or audio exemplar p…

eess.AS2025

DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation

Dongya Jia, Zhuo Chen, Jiawei Chen +8

Several recent studies have attempted to autoregressively generate continuous speech representations without discrete speech tokens by combining diffusion and autoregressive models…

eess.AS2024★ 7 cited

Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

Philip Anastassiou, Jiawei Chen, Jitong Chen +43

We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-T…

eess.AS2022

Zero-Shot Accent Conversion using Pseudo Siamese Disentanglement Network

Dongya Jia, Qiao Tian, Kainan Peng +5

The goal of accent conversion (AC) is to convert the accent of speech into the target accent while preserving the content and speaker identity. AC enables a variety of applications…