Search Results for author:
Found 4 papers, 0 papers with code
Improving the Intelligibility of Electric and Acoustic Stimulation Speech Using Fully Convolutional Networks Based Speech Enhancement
Recently, a time-domain speech enhancement algorithm based on the fully convolutional neural networks (FCN) with a short-time objective intelligibility (STOI)-based objective function (termed FCN(S) in short) has received increasing attention due to its simple structure and effectiveness of restoring clean speech signals from noisy counterparts.
Denoising
Speech Enhancement
+1
Sound
Audio and Speech Processing
Seeing Voices in Noise: A Study of Audiovisual-Enhanced Vocoded Speech Intelligibility in Cochlear Implant Simulation
Speech perception is a key to verbal communication.
Speech Enhancement
Sound
Audio and Speech Processing
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks
For example, in measuring speech intelligibility, most of the evaluation metric is based on a short-time objective intelligibility (STOI) measure, while the frame based minimum mean square error (MMSE) between estimated and clean speech is widely used in optimizing the model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
