本論文提出了兩種應用於數位助聽器的演算法──探討雙麥克風拾音特性與功率譜密度之噪音抑制演算法(A Dual-Microphone Noise Reduction Algorithm Based on Power Level Difference and Polar Pattern)、適用中高度陡降型聽損之非線性頻率壓縮演算法(A Nonlinear Frequency Compression Algorithm to Enhance High Frequency Speech Intelligibility Designed for Moderate and Severe Sloping Hearing Loss)。前者為端射型(Endfire)的雙麥克風系統(Dual-microphone System)，由於助聽器有小體積的基本要求，故兩麥克風的間距需極小，進而導致基於相干性函數(Coherence Function)的表現不佳，改以功率階層差(Power Level Difference, PLD)與拾音特性(Polar Pattern)取代，進一步引入理想二元遮罩(Ideal Binary Mask)的概念，避免過度地抑制已被語音遮蔽的噪音，造成語音訊號變形(Distortion)而影響辨識能力，因此，無論在理想的模擬假設下，抑或是真實錄音環境中，本論文所提出之噪音抑制演算法，即使面對各種類型的噪音源干擾，能在信噪比(Signal to Noise Ratio, SNR)、基於相干性的語音辨識度指標(Coherence-based Speech Intelligibility Index, CSII)上有相當幅度的改善，如此確保本演算法的穩定性，此外，本論文所提出的噪音抑制演算法在運算複雜度的比較上亦佔有優勢，故能為聽損者提供一個效能穩定、體積小，且成本考量上更符合經濟效益的選擇；後者的非線性頻率壓縮演算法的研究對象是中高度的陡降型聽損者(Sloping Hearing Loss)，若僅是純粹地對富含許多重要信息的高音頻帶進行放大處理(Amplification)，並無法帶來等效的助益，還可能導致回授型噪音(Feedback Noise)來影響聽覺感受，所以本論文依照聽損者的聽力圖(Audiogram)、聽力辨識度權重值(Speech Intelligibility Weights)，來客製化地調整各頻帶語音的分布，將高頻資訊保留至較低的頻帶，便可達到節省回授音消除(Feedback Cancellation)的成本，以及提升受測者在華語語音聽力辨識測驗(Mandarin Speech Recognition Test)的表現。綜合上述，本論文兼具數值上的改良，以及符合使用者端真正的需求兩大特點，以祈能為更多的聽損者帶來幫助。

This thesis presents a noise reduction algorithm and a frequency compression method designed for digital hearing aids. The proposed noise reduction is designed as dual microphone endfire configuration. We adopt the power level difference and polar pattern instead of coherence function to decrease the inaccuracy in small-sized applications. Also, an adaptive threshold mechanism and the concept of ideal binary mask are added. It leads to speech intelligibility enhancement with objective measurements SNR and CSII in different noise corrupted environment. Moreover, less adders and multipliers are used in computation complexity comparison.
The frequency compression method is designed for a specific group people with sloping hearing loss. We propose a customized nonlinear frequency compression method rather than amplification in previous work. This method will manipulate the distribution of frequency by user’s audiogram and speech intelligibility weights. Preserving the information in both low frequencies and high frequencies, participants have higher scores on mandarin speech recognition test.
Combining noise reduction and frequency compression in a hearing aids system, this thesis could apply a stable performance on speech perception as well as economical choice for hearing impairments.

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