Speech-in-noise intelligibility improvement based on power recovery and dynamic range compression

The ability to detect speech in noise plays a significant role in our communication with others. In this work we suggest to modify the original speech signal before this is presented in the noisy environment by combining a signal to noise ratio recovery approach with dynamic range compression in order to improve the intelligibility of the speech in noise. The modification is performed under the constraint of equal global signal power before and after modifications. Experiments with speech shaped (SSN) and competing speaker (CS) types of noise at various low SNR values, show that the suggested approach outperforms state-of-the-art methods in terms of the Speech Intelligibility Index (SII) as well as in informal listening tests. Comparing with a state-of-the-art method there is an improvement of 4 dB and 8 dB in terms of SNR gain, for the SSN and the CS types of noise, respectively.