A Reverberation-Time-Aware Approach to Speech Dereverberation Based on Deep Neural Networks

By Bo Wu, Kehuang Li, Minglei Yang, Chin-Hui Lee. 2017

92 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computational Mechanics, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Rongjie Huang

In Computational Mechanics

1. Lei Xie
2. Sining Sun
3. Rongjie Huang

In Signal Processing

1. Dongchao Yang
2. Rongjie Huang
3. Lei Xie
4. Jiatong Shi
5. Jiang Bian
6. Sining Sun
7. Fei Xiang
8. Junbo Zhang

Citations in the corpus

• UniAudio: An Audio Foundation Model Toward Universal Audio Generation (2023, background): “…textual description music Audio Edit (A-Edit) ♣♢ (Wang et al., 2023d) textual description, original sounds sounds Speech dereverberation (SD) ♣♢ (Wu et al., 2016) reverberant speech speech Instruct TTS (I-TTS) ♢ (Guo et al., 2023) phoneme, textual instruction speech Speech Edit (S-Edit) (Tae et…”
• Supervised Speech Separation Based on Deep Learning: An Overview (2017, unknown): “Diagram of a reverberation time aware DNN for speech dereverberation (redrawn from [190]).”
• Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition (2018, background): “Either direct spectral mapping [4, 14] or masking [17] can be considered in the dere-verberation network.”