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Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding
Conventional audio coding technologies commonly leverage human perceptio...
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Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization
Scalability and efficiency are desired in neural speech codecs, which su...
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A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement
In speech enhancement, an end-to-end deep neural network converts a nois...
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Efficient Context Aggregation for End-to-End Speech Enhancement Using a Densely Connected Convolutional and Recurrent Network
In speech enhancement, an end-to-end deep neural network converts a nois...
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Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding
Speech codecs learn compact representations of speech signals to facilit...
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On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising
We present a psychoacoustically enhanced cost function to balance networ...
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A Hybrid Supervised-unsupervised Method on Image Topic Visualization with Convolutional Neural Network and LDA
Given the progress in image recognition with recent data driven paradigm...
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Kai Zhen
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