Assessment of adaptive noise reduction algorithms

自适应降噪算法的评估

• 批准号: 463857-2014
• 负责人: Parsa, Vijay
• 金额: $ 1.82万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=558679
• 关键词: Assessment; adaptive; noise; reduction; algorithms

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.

听力损失是加拿大第三大最常见的慢性残疾，大约10%的加拿大人患有某种形式的听力损失。 助听器是听力损失的主要治疗选择，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到受损的耳朵。在这些DSP功能中，识别和减轻不期望的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理解和跟随背景噪声中的对话方面有更大的困难，因此可以从助听器内的额外声音净化操作中受益。