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

7 citations · 20 across the 18 of their papers we have counts for

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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

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★ 6 cited

Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition

Ye Bai, Jingping Chen, Jitong Chen +52

Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…

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.AS2023

Audio Prompt Tuning for Universal Sound Separation

Yuzhuo Liu, Xubo Liu, Yan Zhao +4

Universal sound separation (USS) is a task to separate arbitrary sounds from an audio mixture. Existing USS systems are capable of separating arbitrary sources, given a few example…

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…

eess.AS2021★ 2 cited

Neural Dubber: Dubbing for Videos According to Scripts

Chenxu Hu, Qiao Tian, Tingle Li +3

Dubbing is a post-production process of re-recording actors' dialogues, which is extensively used in filmmaking and video production. It is usually performed manually by profession…