Assessment of adaptive noise reduction algorithms

听力损失是加拿大第三大最常见的慢性残疾，大约10%的加拿大人受到某种形式的听力损失的影响。助听器是听力损失的主要补救选择，当前一代助听器采用复杂的数字信号处理（DSP）算法，将适当放大的声音传递给受损的耳朵。在这些DSP功能中，识别和减轻不良背景噪声的自适应算法对助听器制造商、听力学家和助听器佩戴者都特别重要。这是由于听力受损的听众在背景噪音中理解和跟随对话的困难更大，因此可以从助听器内额外的声音净化操作中受益。

Hearing loss ranks as the third most prevalent chronic disability in Canada, with approximately 10% of Canadians affected by some form of hearing loss. Hearing aids serve as the primary remedial option for hearing loss, and current generation hearing aids employ sophisticated digital signal processing (DSP) algorithms to deliver appropriately amplified sound to the impaired ear. Among these DSP features, adaptive algorithms that identify and mitigate undesirable background noise are of particular importance to hearing aid manufacturers, Audiologists, and hearing aid wearers alike. This is due to the fact that hearing impaired listeners have greater difficulty in understanding and following conversations in background noise, and therefore stand to benefit from additional sound cleansing operations within the hearing aid.