Microphone array speech denoising modeled by tensor filtering

This paper proposes a novel speech denoising method based on tensor filtering, in which the microphone array speech signal is constructed by tensor data and processed by tensor filtering model. The multi-microphone signal is represented with three-order tensor space in the way of channel, time and frequency. Noise can be reduced by finding the lower-rank approximation of the three-order tensor with tucker model. MDL (Minimum Description Length) criterion is used to estimate the optimal tensor rank. The performance of the proposed approach is evaluated with objective indexes and listening quality test. The experimental results indicate that the proposed approach has potential ability of retrieving the target signal from noisy microphone array signal.