Abstract
This paper investigates the possibility of using complex operations to perform speech enhancement task in time domain. To that end, first, the Hilbert transform is utilized to prepare the complex input in time domain. After that, the complex temporal convolutional network (CTCN) is developed to conduct complex convolutions. By cascading the TCN and the CTCN modules, the final proposed network form an encoder-decoder structure, which performs an end-to-end speech enhancement task. The results demonstrate that utilizing complex information in time domain indeed improves the enhancement performance. Compared to other approaches, the proposed network also demonstrates a superior performance in terms of objective evaluations.
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