
This thesis aims to investigate the phase estimation problem in speech enhancement and dereverberation.
Noise and reverberation widely exist in daily lives, and have detrimental effects on the quality and
In our initial speech dereverberation experiments, we found an issue in the perceptual evaluation
achieved results similar to the estimated phase in terms of the quality of reconstructed speech.
intelligibility of speech for human listeners. Therefore, speech enhancement and dereverberation
of speech quality (PESQ) measure. When measuring reverberant speech, the cross-correlation-based
We also conducted a listening test to measure the perceptual quality of the produced speech, and
the results showed that our proposed WMP loss function is slightly preferred in terms of speech
this loss function led to an increase in speech quality. We then proposed a non-iterative phase
reconstruction approach and an iterative phase reconstruction approach to reconstruct the phase
Speech enhancement, Speech dereverberation, Deep learning, Phase processing
Speech enhancement, Speech dereverberation, Deep learning, Phase processing
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