Light-Weight Speaker Verification with Global Context Information
In this paper, we propose a light-weight speaker verification (SV) system that utilizes the characteristics of utterance-level global features.
Many recent SV tasks employ convolutional neural networks (CNNs) to extract representative speaker features from the given input utterances. However, their inherent receptive field size on the feature extraction process is limited by the localized structure of the convolutional layers.
To effectively extract utterance-level global speaker representations, we introduce a novel architecture combining a CNN with a self-attention network that is able to utilize the relationship between local and aggregated global features. The global features are continuously updated at every analysis block using a point-wise attentive summation to the local features.
We also adopt a densely connected CNN structure (DenseNet) to reliably estimate speaker-related local features with a small number of model parameters. Our proposed model shows higher speaker verification performance with EER 1.935% with significantly small number of parameters, 1.2M, which is 16% reduced model size than the baseline models.
|333||International Conference||Zhenyu Piao, Miseul Kim, Hyungchan Yoon, Hong-Goo Kang "HappyQuokka System for ICASSP 2023 Auditory EEG Challenge" in ICASSP, 2023|
|332||International Conference||Byeong Hyeon Kim, Hyungseob Lim, Jihyun Lee, Inseon Jang, Hong-Goo Kang "Progressive Multi-Stage Neural Audio Codec with Psychoacoustic Loss and Discriminator" in ICASSP, 2023|
|331||International Conference||Hyungseob Lim, Jihyun Lee, Byeong Hyeon Kim, Inseon Jang, Hong-Goo Kang "End-to-End Neural Audio Coding in the MDCT Domain" in ICASSP, 2023|
|330||International Conference||Miseul Kim, Zhenyu Piao, Jihyun Lee, Hong-Goo Kang "Style Modeling for Multi-Speaker Articulation-to-Speech" in ICASSP, 2023|
|329||International Journal||Jinyoung Lee, Hong-Goo Kang "Real-Time Neural Speech Enhancement Based on Temporal Refinement Network and Channel-Wise Gating Methods" in Digital Signal Processing, vol.133, 2023|
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|327||International Journal||Jinyoung Lee, Hong-Goo Kang "Two-Stage Refinement of Magnitude and Complex Spectra for Real-Time Speech Enhancement" in IEEE Signal Processing Letters, vol.29, pp.2188-2192, 2022|
|326||International Conference||Hyeon-Kyeong Shin, Hyewon Han, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang "Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting" in INTERSPEECH (*Best Student Paper Finalist), 2022|
|325||International Conference||Changhwan Kim, Se-yun Um, Hyungchan Yoon, Hong-goo Kang "FluentTTS: Text-dependent Fine-grained Style Control for Multi-style TTS" in INTERSPEECH, 2022|
|324||International Conference||Miseul Kim, Zhenyu Piao, Seyun Um, Ran Lee, Jaemin Joh, Seungshin Lee, Hong-Goo Kang "Light-Weight Speaker Verification with Global Context Information" in INTERSPEECH, 2022|