A fast algorithm for improved intelligibility of speech-in-noise based on frequency and time domain energy reallocation

This paper presents a fast and effective algorithm for enhancing speech intelligibility in additive noise conditions under the constraint of equal signal power before and after enhancement. Speech energy is reallocated in time, using dynamic range compression, and in frequency by boosting the signal to noise ratio in high frequencies, increasing the contrast between consecutive spectral peaks and valleys for the mid-frequencies, while maintaining the spectral energy in low frequencies. The algorithm has 90% lower computational load than similar and recently suggested state-of-the art approaches, while in large formal speech-in-noise intelligibility tests, the algorithm has shown to perform equally well to these methods in terms of intelligibility gains.