Papers
On Fine-Tuning Pre-Trained Speech Models With EMA-Target Self-Supervised Loss
International Conference
2021~
작성자
김병현
작성일
2023-12-14 16:35
조회
1860
However, fine-tuning can degrade the general knowledge that was originally built up by the pre-training, which could help prevent the model from overfitting given sparse fine-tuning data or bridge gaps between different domains.
We hypothesize that preserving this general knowledge in pre-trained models is crucial for improving performance on downstream tasks.
Based on this idea, we propose a novel method for fine-tuning self-supervised speech models that utilizes a self-supervised loss over the course of fine-tuning.
Then, an Exponential Moving Average (EMA) technique is applied to smoothly transition the domain of the model from the generalized to the task-oriented one.
We perform various downstream tasks using the proposed method, finding that our method improves performance on most of the tasks. Results show that our method induces the generalization ability of the model to be retained without overshadowing the downstream task performance.
전체 370
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369 | International Conference | Sangmin Lee, Woojin Chung, Hong-Goo Kang "LAMA-UT: Language Agnostic Multilingual ASR through Orthography Unification and Language-Specific Transliteration" in Association for the Advancement of Artificial Intelligence (AAAI), 2025 | |
368 | International Journal | Hyewon Han, Xiulian Peng, Doyeon Kim, Yan Lu, Hong-Goo Kang "Dual-Branch Guidance Encoder for Robust Acoustic Echo Suppression" in IEEE Transactions on Audio, Speech and Language Processing (TASLP), 2024 | |
367 | International Journal | Hyungseob Lim, Jihyun Lee, Byeong Hyeon Kim, Inseon Jang, Hong-Goo Kang "Perceptual Neural Audio Coding with Modified Discrete Cosine Transform" in IEEE Journal of Special Topics in Signal Processing (JSTSP), 2025 | |
366 | International Conference | Juhwan Yoon, Hyungseob Lim, Hyeonjin Cha, Hong-Goo Kang "StylebookTTS: Zero-Shot Text-to-Speech Leveraging Unsupervised Style Representation" in APSIPA ASC, 2024 | |
365 | International Conference | Doyeon Kim, Yanjue Song, Nilesh Madhu, Hong-Goo Kang "Enhancing Neural Speech Embeddings for Generative Speech Models" in APSIPA ASC, 2024 | |
364 | Domestic Conference | 최웅집, 김병현, 강홍구 "자기 지도 학습 특징을 활용한 음성 신호의 논 블라인드 대역폭 확장" in 대한전자공학회 2024년도 하계종합학술대회, 2024 | |
363 | Domestic Conference | 홍연아, 정우진, 강홍구 "효율적인 양자화 기법을 통한 DNN 기반 화자 인식 모델 최적화" in 대한전자공학회 2024년도 하계종합학술대회, 2024 | |
362 | Domestic Conference | 김병현, 강홍구, 장인선 "저지연 조건하의 심층신경망 기반 음성 압축" in 한국방송·미디어공학회 2024년 하계학술대회, 2024 | |
361 | International Conference | Miseul Kim, Soo-Whan Chung, Youna Ji, Hong-Goo Kang, Min-Seok Choi "Speak in the Scene: Diffusion-based Acoustic Scene Transfer toward Immersive Speech Generation" in INTERSPEECH, 2024 | |