Pitch-Based Voice Activity Detection for Feedback Cancellation and Noise Reduction in Hearing Aids

Abstract

In hearing aid (HA) systems, amplification of speech signals is done to compensate the hearing loss of patients. Background noise and feedback signals may also get amplified which degrade the intelligibility and quality of speech. To achieve high de-noise efficiency, signal processing unit in HA system has voice activity detector (VAD). The conventional VAD detects voice based on zero crossing rate or energy of input signals. However, these methods cannot perform well at low SNR or non-stationary noise environments. Since pitch is a special characteristic of speech and is basically independent of noise intensity, VAD based on pitch can have high accuracy even when the noise spectrum is changing drastically. In this paper, pitch-based VAD is presented and its accuracy is checked against zero crossing rate-based VAD (ZCR-VAD). For noise reduction, an improved multi-band spectral over-subtraction algorithm is employed along with the high accurate pitch-based VAD. For feedback cancellation, the performance of adaptive algorithms like NLMS, RLS and affine projection (AP) algorithms with pitch-based VAD is compared and it is observed that AP is suitable for feedback cancellation. The proposed noise reduction and feedback cancellation algorithm with pitch-based VAD method is tested with NOIZEUS speech database and with real-time noisy speech signals. The simulation results show that the accuracy of pitch-VAD is about 23% higher than that of ZCR-VAD. The SNR for the proposed noise reduction and feedback cancellation with pitch-VAD method is improved by 10 dB than conventional spectral subtraction and adaptive algorithms. Mean opinion score (MOS) obtained for the proposed method is 4.3 out of 5.