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
1676
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 367
25 | International Conference | Hejung Yang, Hong-Goo Kang "On Fine-Tuning Pre-Trained Speech Models With EMA-Target Self-Supervised Loss" in ICASSP, 2024 | |
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23 | International Conference | Hong-Goo Kang, Jan Skoglund, W. Bastiaan Kleijn, Andrew Storus, Hengchin Yeh "A High-Rate Extension to Soundstream" in IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2023 | |
22 | International Conference | Zhenyu Piao, Hyungseob Lim, Miseul Kim, Hong-goo Kang "PDF-NET: Pitch-adaptive Dynamic Filter Network for Intra-gender Speaker Verification" in APSIPA ASC, 2023 | |
21 | International Conference | Miseul Kim, Zhenyu Piao, Jihyun Lee, Hong-Goo Kang "BrainTalker: Low-Resource Brain-to-Speech Synthesis with Transfer Learning using Wav2Vec 2.0" in The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2023 | |
20 | International Conference | Seyun Um, Jihyun Kim, Jihyun Lee, Hong-Goo Kang "Facetron: A Multi-speaker Face-to-Speech Model based on Cross-Modal Latent Representations" in EUSIPCO, 2023 | |
19 | International Conference | Hejung Yang, Hong-Goo Kang "Feature Normalization for Fine-tuning Self-Supervised Models in Speech Enhancement" in INTERSPEECH, 2023 | |
18 | International Conference | Jihyun Kim, Hong-Goo Kang "Contrastive Learning based Deep Latent Masking for Music Source Seperation" in INTERSPEECH, 2023 | |
17 | International Conference | Woo-Jin Chung, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang "MF-PAM: Accurate Pitch Estimation through Periodicity Analysis and Multi-level Feature Fusion" in INTERSPEECH, 2023 | |
16 | International Conference | Hyungchan Yoon, Seyun Um, Changhwan Kim, Hong-Goo Kang "Adversarial Learning of Intermediate Acoustic Feature for End-to-End Lightweight Text-to-Speech" in INTERSPEECH, 2023 | |