A low-complexity voice activity detector for smart hearing protection of hyperacusic persons

In this paper, a Voice Activity Detector (VAD) is proposed for smart hearing protection applications where speech is to get through the hearing protector while ambient noise is to be blocked out. The VAD calculates a short-term statistical assessment of the temporal envelopes within different frequency bands. This assessment uses the Inter-Quartile Range (IQR) and reflects the dispersion of the envelopes’ magnitudes. The VAD’s decision is made using two threshold comparison rules and a hangover scheme triggered after a given number of observations. These four parameters have been optimized off-line using a genetic algorithm approach. The performance of the proposed VAD is compared to Sohn’s VAD using a database of 90 speech signals corrupted by five real-world noise environments at Signal-to-Noise ratios (SNR) varying from 0 to +10 dB. Results show that the proposed VAD performs better than Sohn’s VAD with an 85.9% (compared to 77.5%) F1 score averaged across all SNRs and also minimizes by a factor of three the mid-speech clipping rate. In addition, the evaluation of the proposed VAD’s computational cost shows that its implementation on-board a low-power low-consumption DSP is very feasible and would enable smart hearing protection for hypersensitive persons.