gmkim90/AAS_enhancement

This repository contains the code and supplementary result for the paper "Unpaired Speech Enhancement by Acoustic and Adversarial Supervision" (IEEE Signal Processing Letters, 2019). We modify the feature from spectrogram to log-Mel filterbank output (LMFB), and 2D convolutional layer to 1D convolutional layer. We trained acoustic model on Librispeech corpus. Generate grapheme probability estimated from the acoustic model on validation data. Find the optimal (alpha, beta) which achieves the lowest WER on the validation data. We search (alpha, beta) by 6x6 grid search.