| Summary: | 博士 === 國立交通大學 === 電子研究所 === 101 === With the advanced digital technology and signal processing, digital hearing aids have more potential to provide good performance to improve user usage experience. However, these sophisticated signal processing algorithms are still hard to be integrated due to the limitation of battery size and capacity, which demands efficient low power algorithm, architecture and circuit design. Thus, this dissertation proposes low power designs for two fundamental blocks of hearings aids: noise reduction (NR) and feedback cancellation (FC).
The proposed NR designs are based on perceptual decomposition for efficient processing. The first NR design adopts a mixed frequency decomposition in conjunction with an efficient spectral subtraction and VAD (voice activity detection) for ultra low power noise suppression. The design can achieve about 4dB SNR improvement in low SNR environment and only consumes 0.65μW at 1.0V operation using 0.18μm process. However, this design adopts a simple scheme for NR, thus not providing good perceptual performance. To solve this problem, the second NR proposes an efficient multiband spectral subtraction design by using sample based processing, data preprocessing scheme and other sophisticated strategies to meet low power and low latency requirement. This design can achieve robust sound quality improvement in terms of SNR, PESQ and composite measure with 83.7μW at 0.6V operation with 90nm HVT (high VT) standard cell library. The performance of the second design is limited by the accuracy of entropy VAD in low SNR and nonstationary environment. To solve this problem, the third design proposes an efficient pitch based VAD for robust voice detection to assist noise suppression. This VAD has an efficient structure and is robust even in nonstationary environment. Based on this VAD, the noise suppression can provide 4dB SNR improvement with 55.52μW at 0.5V operation with 0.65μm high VT process.
The pitch based processing is further applied to FC design which uses pitch results to estimate speech formant to enhance the robustness and the sound quality of adaptive feedback cancellation (AFC). The proposed AFC design can achieve similar added stable gain (ASG) and PESQ but with five orders complexity reduction compared to conventional designs. Based on the pitch based information, this dissertation also proposes an efficient pitch based processor for further system development.
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