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• W3160747466 abstract "We present MarbleNet, an end-to-end neural network for Voice Activity Detection (VAD). MarbleNet is a deep residual network composed from blocks of 1D time-channel separable convolution, batch-normalization, ReLU and dropout layers. When compared to a state-of-the-art VAD model, MarbleNet is able to achieve similar performance with roughly 1/10-th the parameter cost. We further conduct extensive ablation studies on different training methods and choices of parameters in order to study the robustness of MarbleNet in real-world VAD tasks." @default.
• W3160747466 created "2021-05-24" @default.
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• W3160747466 date "2021-06-06" @default.
• W3160747466 modified "2023-09-30" @default.
• W3160747466 title "MarbleNet: Deep 1D Time-Channel Separable Convolutional Neural Network for Voice Activity Detection" @default.
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• W3160747466 doi "https://doi.org/10.1109/icassp39728.2021.9414470" @default.
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