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Speech enhancement for hearing instruments: Enabling communication in adverse conditions

机译:助听器的语音增强:在不利条件下进行交流

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Hearing instruments are frequently used in notoriously difficult acoustic scenarios. Even for normal-hearing people ambient noise, reverberation and echoes often contribute to a degraded communication experience. The impact of these factors becomes significantly more prominent when participants suffer from a hearing loss. Nevertheless, hearing instruments are frequently used in these adverse conditions and must enable effortless communication. In this talk I will discuss challenges that are encountered in acoustic signal processing for hearing instruments. While many algorithms are motivated by the quest for a cocktail party processor and by the high-level paradigms of auditory scene analysis a careful design of statistical models and processing schemes is necessary to achieve the required performance in real world applications. Rather strict requirements result from the size of the device, the power budget, and the admissable processing latency. Starting with low-latency spectral analysis and synthesis systems for speech and music signals I will continue highlighting statistical estimation and smoothing techniques for the enhancement of noisy speech. The talk emphasizes the necessity to find a good balance between temporal and spectral resolution, processing latency, and statistical estimation errors. It concludes with single and multi-channel speech enhancement examples and an outlook towards opportunities which reside in the use of comprehensive speech processing models and distributed resources.
机译:听力仪器经常用于臭名昭着的声学情景。即使对于正常听到的人们,环境噪音,混响和回声通常会导致较大的通信经验。当参与者遭受听力损失时,这些因素对这些因素的影响变得显着更加突出。尽管如此,听力仪器经常用于这些不利条件,并且必须实现轻松的沟通。在此谈话中,我将讨论用于听力仪器的声学信号处理中遇到的挑战。虽然许多算法是通过寻求鸡尾酒会处理器的驱动,但是通过听觉场景分析的高级范式分析,仔细设计统计模型和处理方案是在现实世界应用中实现所需性能的统计设计。相当严格的要求由设备的大小,电源预算和允许的处理延迟产生。从低延迟光谱分析和综合系统开始,用于语音和音乐信号,我将继续突出统计估算和平滑技术,以提高嘈杂的语音。谈话强调必须在时间和光谱分辨率,处理延迟和统计估计错误之间找到良好的平衡。它与单通道和多通道语音增强例子以及驻留在使用综合语音处理模型和分布式资源的机会的展望。

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