Schedule
MINDS SEMINAR
MINDS Seminar Series | Il Youp Kwak (Chung Ang University) - Low-quality Fake Audio Detection through Frequency Feature Masking
MINDS SEMINAR
period : 2022-11-01 ~ 2022-11-01
time : 17:00:00 ~ 18:00
개최 장소 : Online streaming (Zoom)
Topic : Low-quality Fake Audio Detection through Frequency Feature Masking
개요
| Date | 2022-11-01 ~ 2022-11-01 | Time | 17:00:00 ~ 18:00 |
| Speaker | Il Youp Kwak | Affiliation | Chung Ang University |
| Place | Online streaming (Zoom) | Streaming link | ID : 688 896 1076 / PW : 54321 |
| Topic | Low-quality Fake Audio Detection through Frequency Feature Masking | ||
| Contents | The first Audio Deep Synthesis Detection Challenge (ADD 2022) competition was held which dealt with audio deepfake detection, audio deep synthesis, audio fake game, and adversarial attacks. Our team participated in track 1, classifying bona fide and fake utterances in noisy environments. Through exploratory data analysis, we found that noisy signals appear in similar frequency bands for given voice samples. If a model is trained to rely heavily on information in frequency bands where noise exists, performance will be poor. In this paper, we propose a data augmentation method, Frequency Feature Masking (FFM) that randomly masks frequency bands. FFM makes a model robust by not relying on specific frequency bands and prevents overfitting. We applied FFM and mixup augmentation on five spectrogram-based deep neural network architectures that performed well for spoofing detection using mel-spectrogram and constant Q transform (CQT) features. Our best submission achieved 23.8% in EER and ranked 3rd on track 1. To demonstrate the usefulness of our proposed FFM augmentation, we further experimented with FFM augmentation using ASVspoof 2019 Logical Access (LA) datasets. | ||
MinDS
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2022-10-04 10:21 ·
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