Speech separation based on reliable binaural cues with two-stage neural network in noisy-reverberant environments

Preserving the beamforming effect for spatial cue-based pseudo-binaural dereverberation of a single source

“…Marginalizing over all sources and all delays, the log likelihood function for DP is given as in (16).…”

“…With the development of Neural Networks (NNs), there has been tremendous improvement in a variety of speech recognition and acoustic signal processing tasks [16]. The binaural dereverberation models in [8], [16] and [17] uses artificial neural network (ANN) for binaural dereverberation preprocessing, the model in [18] uses the recurrent neural network (RNN) and interaural cues for speech enhancement in reverberant noisy conditions, while the models in [19] and [20] use the U-Net (a deep convolutional neural network (CNN)) for dereverberation, but these are monaural models.…”

Application practice of neural network algorithms in speech recognition technology

“…Due to the interference of external noise and the instability of speech signals, traditional SR methods are difficult to achieve high accuracy and robustness, and it is also difficult to achieve the expected performance in practical applications 9 . In recent years, due to the significant improvement in computer computing performance and the rise of DL, research on SR has also made tremendous progress 10 .…”