Abstract: Acoustic features play an important role in improving the quality of the synthesised speech. Currently, the Mel spectrogram is a widely employed acoustic feature in most acoustic models.

Abstract: In this study, we extend the capability of the method of relative-to-maximum masking (RMM) in speech enhancement by further leveraging the importance of each time-frequency unit in the ...

We incorporate effective components of the TasNet into a freq-domain separation method. We introduce a solution for directly optimizing the separation criterion in freq-domain networks. Our exp ...

Patients suffering from Parkinson's disease suffer from voice impairment. In this study, we introduce models to classify normal and Parkinson's patients using their speech. We used an AST (audio ...

Advanced Speech Emotion Detection (SED) using spectrogram analysis and deep learning offers a nuanced and accurate method for interpreting human emotions from speech. By transforming raw speech data ...