Weighting Time-Frequency Representation of Speech Using Auditory Saliency for Automatic Speech Recognition

@inproceedings{Do2018WeightingTR,
  title={Weighting Time-Frequency Representation of Speech Using Auditory Saliency for Automatic Speech Recognition},
  author={Cong-Thanh Do and Yannis Stylianou},
  booktitle={INTERSPEECH},
  year={2018}
}
This paper proposes a new method for weighting twodimensional (2D) time-frequency (T-F) representation of speech using auditory saliency for noise-robust automatic speech recognition (ASR). Auditory saliency is estimated via 2D auditory saliency maps which model the mechanism for allocating human auditory attention. These maps are used to weight T-F representation of speech, namely the 2D magnitude spectrum or spectrogram, prior to features extraction for ASR. Experiments on Aurora-4 corpus… 
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