End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks

Understand

Speech enhancement model is used to map a noisy speech to a clean speech.

• In the training stage, an objective function is often adopted to optimize the model parameters.
• However, in most studies, there is an inconsistency between the model optimization criterion and the evaluation criterion on the enhanced speech.
• 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.