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Single channel speech dereverberation is considered in this work. Inspired bythe recent success of Bidirectional Encoder Representations from Transformers(BERT) model in the domain of Natural Language Processing (NLP), we investigateits applicability as backbone sequence model to enhance reverberated speechsignal. We present a variation of the basic BERT model: a pre-sequence network,which extracts local spectral-temporal information and/or provides orderinformation, before the backbone sequence model. In addition, we usepre-trained neural vocoder for implicit phase reconstruction. To evaluate ourmethod, we used the data from the 3rd CHiME challenge, and compare our resultswith other methods. Experiments show that the proposed method outperformstraditional method WPE, and achieve comparable performance withstate-of-the-art BLSTM-based sequence models.

Translate Reverberated Speech to Anechoic Ones: Speech Dereverberation with BERT