FiLM Conditioning with Enhanced Feature to the Transformer-based End-to-End Noisy Speech Recognition. - Da-Hee Yang; Joon-Hyuk Chang (INTERSPEECH, 2022)

Towards Robust Packet Loss Concealment System With ASR-Guided Representations. - Da-Hee Yang; Joon-Hyuk Chang (ASRU, 2023)

Selective Film Conditioning with CTC-Based ASR Probability for Speech Enhancement. - Da-Hee Yang; Joon-Hyuk Chang (ICASSP, 2023)

Masked Frequency Modeling for Improving Packet Loss Concealment in Speech Transmission Systems. - Da-Hee Yang; Donghyun Kim; Joon-Hyuk Chang (WASPAA, 2023)

Attention-based latent features for jointly trained end-to-end automatic speech recognition with modified speech enhancement. - Da-Hee Yang; Joon-Hyuk Chang (J. King Saud Univ. Comput. Inf. Sci., 2023)

Guided conditioning with predictive network on score-based diffusion model for speech enhancement. - Dail Kim; Da-Hee Yang; Donghyun Kim; Joon-Hyuk Chang; Jeonghwan Choi; Moa Lee; Jaemo Yang; Han-gil Moon (INTERSPEECH, 2024)

Diff-PLC: A Diffusion-Based Approach For Effective Packet Loss Concealment. - Da-Hee Yang; Joon-Hyuk Chang (SLT, 2024)

DM: Dual-path Magnitude Network for General Speech Restoration. - Da-Hee Yang; Dail Kim; Joon-Hyuk Chang; Jeonghwan Choi; Han-gil Moon (CoRR, 2024)

Flow-PLC: Towards Efficient Packet Loss Concealment With Flow Matching. - Da-Hee Yang; Joon-Hyuk Chang (IEEE Signal Process. Lett., 2025)

Tokenized Generative Speech Enhancement With Language Model and Flow Matching. - Da-Hee Yang; Jaeuk Lee; Joon-Hyuk Chang (IEEE Signal Process. Lett., 2025)

FLOWER: Flow-Based Estimated Gaussian Guidance for General Speech Restoration. - Da-Hee Yang; Jaeuk Lee; Joon-Hyuk Chang (CoRR, 2025)