- 學位論文
應用平穩小波係數臨界值去噪法於濾除數位助聽器之雜訊
On the Application of the De-noising Method of Stationary Wavelet Coefficients Threshold to Filter Out Noise in Digital Hearing Aids
摘要
長久以來，對於如何改善聽障人士的聽覺損失，一直是研究人員與醫學界極力想要改善的目標。尤其目前全球大約有兩億五千個聾人或者是重聽人士，所以對於研究人員與醫學界來說這個目標還是有它的重要性。所幸拜科技發展所賜，從早期的類比助聽器到目前主流的數位助聽器。各種數位訊號處理的技術蓬勃發展，目前的助聽器的功能已不在是單純的直接將聲音放大讓聽障人士聆聽，可以依照不同使用者的不同需求，進行不同的聲音訊號處理。但是其實助聽器的發展仍有許多進步的空間。 本文先將乾淨的語音訊號加入白雜訊，成為包含雜訊的語音訊號。再分別使用離散小波轉換與離散平穩小波轉換，先將語音頻帶切割為9個不同帶寬的次頻帶，再使用小波包轉換將語音頻帶切割為8個相同帶寬的次頻帶。然後使用小波去噪法將高頻雜訊的部份濾除，再將去噪過後的語音訊號分別補償四種不同型式的聽力損失，包含40dB平坦損失、輕度低頻損失、中度高頻損失、重度高頻損失。最後再考慮到飽和音量的限制，將最後輸出的語音限制在固定的能量大小。藉由模擬小波轉換在語音訊號處理的過程，驗證可以有效的濾除白雜訊，也可以補償四種不同型式的聽力損失，達到基本數位助聽器的功能。
並列摘要
For a long time, improving the hearing of the hearing-impaired has been what researchers and medical professionals been struggling to achieve. Because there are currently over 200 million deaf or hard of hearing people worldwide, researchers and medical professionals realize the importance of this goal. Fortunately, the gift of technology, from early analog hearing aids to the mainstream of digital hearing aids, has brought about various kinds of flourishing digital signal processing technology. The function of current hearing aids is no longer restricted to just simple voice amplification, which allows the hearing-impaired to hear directly, but can also satisfy the different needs of different users with different sound signal processing. In fact, the development of hearing aids still has an opportunity for improvement. In this paper, the white noise is added to the clean voice signal, becoming a voice signal that contains noise. First, the discrete wavelet transform is used to cut the voice bandwidth into nine different sub-band bandwidths. Second, the discrete wavelet stationary transform is used to cut the voice bandwidth into nine different sub-band bandwidths. Third, the wavelet packet transform is used to cut the voice bandwidth into eight identical bandwidths. The wavelet de-noising method is used to filter out high-frequency noise. After the voice signal has been de-noised, it makes up four different types of hearing loss, including 40dB uniform hearing loss, mild low-frequency hearing loss, moderate high-frequency hearing loss, and severe high-frequency hearing loss. Finally, the saturated volume limits the final output of the energy of speech to a fixed size. This thesis is to simulate voice signal processing by the wavelet transform. The process of verification can effectively filter out white noise, and compensate the four different types of hearing loss to achieve the basic functions of digital hearing aids.