Jaesung Bae

I am a PhD student in the Computer Science (CS) Department at the University of Illinois Urbana-Champaign, advised by Prof. Minje Kim and Prof. Paris Smaragdis. My current research interests include speech and audio representation learning, as well as data augmentation methods for low-resource and underrepresented domains in speech and audio.
   In the summer of 2025, I had the privilege of working as a Research Scientist Intern on the Meta Superintelligence Lab. My project focused on enhancing the understanding and generation capabilities of full-duplex and multimodal (speech and text) large language models. Previously I worked as a speech AI researcher at Samsung Research, where my main research topics included personalized and zero-shot on-device TTS systems. I am proud to have contributed to the TTS systems integrated in the Galaxy S24. Before that, I was at NCSOFT, a game company, where I primarily studied expressive TTS and prosody controllable TTS systems. I earned my MS in Electrical Engineering from KAIST, where I was advised by Prof. Daeshik Kim in the BREIL lab, and my BS in Electrical and Electronic Engineering from Yonsei University.

   Below shows my projects, publications, invited talks, and academic services. Please refere to my CV for further details.

*: Equal Contribution

Generative Data Augmentation Challenge: Zero-Shot Speech Synthesis for Personalized Speech Enhancement
Jae-Sung Bae, Anastasia Kuznetsova, Dinesh Manocha, John Hershey, Trausti Kristjansson, and Minje Kim
In Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Workshops (ICASSPW): Generative Data Augmentation for Real-World Signal Processing Applications (GenDA 2025), 2025.
[paper] [code] [website]

Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis
Jae-Sung Bae, Joun Yeop Lee, Ji-Hyun Lee, Seongkyu Mun, Taehwa Kang, Hoon-Young Cho, Chanwoo Kim
In Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2024.
[paper] [demo]

MELS-TTS : Multi-Emotion Multi-Lingual Multi-Speaker Text-to-Speech System via Disentangled Style Tokens
Heejin Choi, Jae-Sung Bae, Joun Yeop Lee, Seongkyu Mun, Jihwan Lee, Hoon-Young Cho, Chanwoo Kim
In Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2024.

Hierarchical Timbre-Cadence Speaker Encoder for Zero-shot Speech Synthesis
Joun Yeop Lee, Jae-Sung Bae, Seongkyu Mun, Jihwan Lee, Ji-Hyun Lee, Hoon-Young Cho, Chanwoo Kim
In Proc. INTERSPEECH, 2023.
[paper] [demo]

Avocodo: Generative Adversarial Network for Artifact-free Vocoder
Taejun Bak, Junmo Lee, Hanbin Bae, Jinhyeok Yang, Jae-Sung Bae, Young-Sun Joo
In Proc. AAAI, 2023.
[paper] [demo] [code]

Hierarchical and Multi-Scale Variational Autoencoder for Diverse and Natural Non-Autoregressive Text-to-Speech
Jae-Sung Bae, Jinhyeok Yang, Tae-Jun Bak, Young-Sun Joo
In Proc. INTERSPEECH, 2022.
[paper] [demo] [video]

Into-TTS : Intonation Template Based Prosody Control System
Jihwan Lee, Joun Yeop Lee, Heejin Choi, Seongkyu Mun, Sangjun Park, Jae-Sung Bae, Chanwoo Kim
arXiv preprint arXiv:2204.01271, 2022.
[paper] [demo]

Hierarchical Context-Aware Transformers for Non-Autoregressive Text to Speech
Jae-Sung Bae, Tae-Jun Bak, Young-Sun Joo, and Hoon-Young Cho
In Proc. INTERSPEECH, 2021.
[paper] [demo]

GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis
Jinhyeok Yang*, Jae-Sung Bae*, Taejun Bak, Youngik Kim, and Hoon-Young Cho
In Proc. INTERSPEECH, 2021.
[paper] [demo]

FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis
Taejun Bak, Jae-Sung Bae, Hanbin Bae, Young-Ik Kim, and Hoon-Young Cho
In Proc. INTERSPEECH, 2021.
[paper] [demo]

A Neural Text-to-Speech Model Utilizing Broadcast Data Mixed with Background Music
Hanbin Bae, Jae-Sung Bae, Young-Sun Joo, Young-Ik Kim, and Hoon-Young Cho
In Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2021.
[paper] [demo]

Speaking Speed Control of End-to-End Speech Synthesis using Sentence-Level Conditioning
Jae-Sung Bae, Hanbin Bae, Young-Sun Joo, Junmo Lee, Gyeong-Hoon Lee, Hoon-Young Cho
In Proc. INTERSPEECH, 2020.
[paper] [demo] [video]

End-to-End Speech Command Recognition with Capsule Network
Jae-Sung Bae, Dae-Shik Kim
In Proc. INTERSPEECH, 2018.
[paper]

You can click each project and check demos and further information.

On-device TTS System in various languages for Galaxy S24's Live Translation
Mar 2023 - Jan 2024 (@Samsung Research)

I contributed to the research and development of an on-device TTS system in eight different languages, which is included as a Live Translation feature and introduced as a main AI feature in the Galaxy S24. My contribution involved enhancing the model architecture and achieving a high-quality TTS system that supports various languages with a reduced model size.

On-device Personalized TTS System for Bixby Custom Voice Creation
May 2022 - Jan 2024 (@Samsung Research)

I contributed to the research and development of an on-device personalized TTS system, which was integrated into Samsung Galaxy Bixby's Custom Voice Creation and utilized within Bixby Text-call functionality. This system can create a personalized TTS system by fine-tuning the TTS directly on the user’s device with just 10 utterances.

Fine-grained Prosody Control of TTS System (prototype web service)
Mar 2021 - Apr 2022 (@NCSOFT)

I conducted research and developed a TTS system that is capable of controlling the prosody of speech in a fine-grained level. With this system, users were able to modify the speech to have desired prosody. This system is released as an in-company web service and was widely used to make an guide videos of NCSOFT's game.

TTS System for K-pop Fandom Platform, “UNIVERSE” (live service)
Mar 2019 - Apr 2022 (@NCSOFT)

I contributed to the research and development of a multi-speaker TTS system replicating the voices of numerous K-pop artists, approximately 100 in total, within a single TTS system. This TTS system was used in "UNIVERSE" service, which is a K-pop fan community platform.

TTS System in Baseball Broadcast Scenario
Mar 2019 - Mar 2021 (@NCSOFT)

I researched and developed an expressive TTS system that can generate speech with dynamic expressions suitable for diverse baseball situations. I published several demos on NCSOFT’s official blog and news articles. Kindly recommand to click this project, and see the demo videos.

End-to-End Speech Command Recognition with Capsule Network
NAVER Corp., Seong-Nam, Republic of Korea
Sep 2018