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Pcf: Ecapa-tdnn with progressive channel fusion for speaker verification
ECAPA-TDNN is currently the most popular TDNN-series model for speaker verification,
which refreshed the state-of-the-art (SOTA) performance of TDNN models. However, one …
which refreshed the state-of-the-art (SOTA) performance of TDNN models. However, one …
Studying squeeze-and-excitation used in CNN for speaker verification
In speaker verification, the extraction of voice representations is mainly based on the
Residual Neural Network (ResNet) architecture. ResNet is built upon convolution layers …
Residual Neural Network (ResNet) architecture. ResNet is built upon convolution layers …
[HTML][HTML] Explore long-range context features for speaker verification
Multi-scale context information, especially long-range dependency, has shown to be
beneficial for speaker verification (SV) tasks. In this paper, we propose three methods to …
beneficial for speaker verification (SV) tasks. In this paper, we propose three methods to …
EcoSpeak: Cost-Efficient Bias Mitigation for Partially Cross-Lingual Speaker Verification
Linguistic bias is a critical problem concerning the diversity, equity, and inclusiveness of
Natural Language Processing tools. The severity of this problem intensifies in security …
Natural Language Processing tools. The severity of this problem intensifies in security …
Progressive channel fusion for more efficient TDNN on speaker verification
ECAPA-TDNN is one of the most popular TDNNs for speaker verification. While most of the
updates pay attention to building precisely designed auxiliary modules, the depth-first …
updates pay attention to building precisely designed auxiliary modules, the depth-first …
Speaker Verification Uasing Spatial Attention Mechanism And Semantic Enhancement
P Li, X Liu, W Suqin, X **e - 2024 43rd Chinese Control …, 2024 - ieeexplore.ieee.org
This paper introduces a novel speaker verification model that enhances the performance of
convolution-driven speaker recognition models. The proposed model incorporates a new …
convolution-driven speaker recognition models. The proposed model incorporates a new …
Back-ends Selection for Deep Speaker Embeddings
Probabilistic Linear Discriminant Analysis (PLDA) was the dominant and necessary back-
end for early speaker recognition approaches, like i-vector and x-vector. However, with the …
end for early speaker recognition approaches, like i-vector and x-vector. However, with the …
I4U System Description for NIST SRE'20 CTS Challenge
This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition
Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's …
Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's …